Uses of Interface
net.finmath.stochastic.RandomVariable

Packages that use RandomVariable

Package	Description
net.finmath.functions	Provides some static functions, e.g., analytic valuation formulas or functions from linear algebra.
net.finmath.marketdata2.calibration	Provides classes to create a calibrated model of curves from a collection of calibration products and corresponding target values.
net.finmath.marketdata2.interpolation	Basic methodologies to interpolate of curves and surfaces are provided here.
net.finmath.marketdata2.model	Provides interface specification and implementation of a model, which is essentially a collection of curves.
net.finmath.marketdata2.model.curves	Provides interface specification and implementation of curves, e.g., interest rate curves like discount curves and forward curves.
net.finmath.marketdata2.products	Provides interface specification and implementation of products, e.g., calibration products.
net.finmath.modelling.productfactory	Provides classes to build products from descriptors.
net.finmath.montecarlo	Provides basic interfaces and classes used in Monte-Carlo models (like LIBOR market model or Monte-Carlo simulation of a Black-Scholes model), e.g., the Monte-Carlo random variable and the Brownian motion.
net.finmath.montecarlo.assetderivativevaluation	Monte-Carlo models for asset value processes, like the Black Scholes model.
net.finmath.montecarlo.assetderivativevaluation.models	Equity models implementing ProcessModel e.g. by extending AbstractProcessModel.
net.finmath.montecarlo.assetderivativevaluation.products	Products which may be valued using an AssetModelMonteCarloSimulationModel.
net.finmath.montecarlo.automaticdifferentiation	Provides classes adding automatic differentiation capabilities to objects relying on RandomVariable objects.
net.finmath.montecarlo.automaticdifferentiation.backward	Provides the implementation of backward automatic differentiation.
net.finmath.montecarlo.automaticdifferentiation.forward	Provides the implementation of forward automatic differentiation.
net.finmath.montecarlo.conditionalexpectation	Algorithms to perform the calculation of conditional expectations in Monte-Carlo simulations, also known as "American Monte-Carlo".
net.finmath.montecarlo.crosscurrency	Provides classes for Cross-Currency models to be implemented via Monte-Carlo algorithms from net.finmath.montecarlo.process.
net.finmath.montecarlo.hybridassetinterestrate	Provides interfaces and classes needed to generate a Hybrid Asset LIBOR Market Model.
net.finmath.montecarlo.hybridassetinterestrate.products	Provides classes which implement financial products which may be valued using a net.finmath.montecarlo.hybridassetinterestrate.HybridAssetLIBORModelMonteCarloSimulation.
net.finmath.montecarlo.interestrate	Provides classes needed to generate a LIBOR market model (using numerical algorithms from net.finmath.montecarlo.process.
net.finmath.montecarlo.interestrate.models	Interest rate models implementing ProcessModel e.g. by extending AbstractProcessModel.
net.finmath.montecarlo.interestrate.models.covariance	Contains covariance models and their calibration as plug-ins for the LIBOR market model and volatility and correlation models which may be used to build a covariance model.
net.finmath.montecarlo.interestrate.products	Provides classes which implement financial products which may be valued using a net.finmath.montecarlo.interestrate.LIBORModelMonteCarloSimulationModel.
net.finmath.montecarlo.interestrate.products.components	Provides a set product components which allow to build financial products by composition.
net.finmath.montecarlo.interestrate.products.indices	Provides a set of indices which can be used as part of a period.
net.finmath.montecarlo.model	Provides an interface and a base class for process models, i.e., models providing the parameters for stochastic processes.
net.finmath.montecarlo.process	Interfaced for stochastic processes and numerical schemes for stochastic processes (SDEs), like the Euler scheme.
net.finmath.montecarlo.process.component.barrier	Components providing the barrier in the Monte-Carlo simulation with barrier.
net.finmath.montecarlo.process.component.factordrift	Components providing the factor drift in the simulation of a proxy simulation scheme.
net.finmath.montecarlo.products	Products which are model independent, but assume a Monte-Carlo simulation.
net.finmath.montecarlo.templatemethoddesign	Legacy classes related to Monte-Carlo simulation - used for teaching only.
net.finmath.montecarlo.templatemethoddesign.assetderivativevaluation	Legacy classes related to Monte-Carlo simulation - used for teaching only.
net.finmath.optimizer	This package provides classes with numerical algorithm for optimization of an objective function and a factory to easy construction of the optimizers.
net.finmath.stochastic	Interfaces specifying operations on random variables.

Uses of RandomVariable in net.finmath.functions

Methods in net.finmath.functions that return RandomVariable

Modifier and Type	Method	Description
static RandomVariable	BachelierModel.bachelierHomogeneousOptionDelta(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit)	Calculates the option delta dV(0)/dS(0) of a call option, i.e., the payoff V(T)=max(S(T)-K,0), where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(rt) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma / N(T) \mathrm{d}W(t) \text{
static RandomVariable	BachelierModel.bachelierHomogeneousOptionValue(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit)	Calculates the option value of a call, i.e., the payoff max(S(T)-K,0), where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(rt) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma / N(T) \mathrm{d}W(t) \text{
static RandomVariable	BachelierModel.bachelierHomogeneousOptionVega(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit)	Calculates the vega of a call, i.e., the payoff max(S(T)-K,0) P, where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(rt) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma / N(T) \mathrm{d}W(t) \text{
static RandomVariable	BachelierModel.bachelierInhomogeneousOptionDelta(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit)	Calculates the option delta dV(0)/dS(0) of a call option, i.e., the payoff V(T)=max(S(T)-K,0), where S follows a normal process with constant volatility, i.e., a inhomogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma exp(r (T-t)) \mathrm{d}W(t) \text{
static RandomVariable	BachelierModel.bachelierInhomogeneousOptionValue(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit)	Calculates the option value of a call, i.e., the payoff max(S(T)-K,0), where S follows a normal process with constant volatility, i.e., a inhomogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma exp(r (T-t)) \mathrm{d}W(t) \text{
static RandomVariable	BachelierModel.bachelierInhomogeneousOptionVega(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit)	Calculates the vega of a call, i.e., the payoff max(S(T)-K,0) P, where S follows a normal process with constant volatility, i.e., a Inhomogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp( r t ) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma exp(-r t) \mathrm{d}W(t) \text{
static RandomVariable	BachelierModel.bachelierOptionDelta(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit)	Calculates the option delta dV(0)/dS(0) of a call option, i.e., the payoff V(T)=max(S(T)-K,0), where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(-r (T-t)) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma \mathrm{d}W(t) \text{
static RandomVariable	AnalyticFormulas.bachelierOptionValue(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit)	Calculates the option value of a call, i.e., the payoff max(S(T)-K,0), where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(-r (T-t)) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma \mathrm{d}W(t) \text{
static RandomVariable	BachelierModel.bachelierOptionValue(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit)	Calculates the option value of a call, i.e., the payoff max(S(T)-K,0), where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(-r (T-t)) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma \mathrm{d}W(t) \text{
static RandomVariable	BachelierModel.bachelierOptionVega(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit)	Calculates the vega of a call, i.e., the payoff max(S(T)-K,0) P, where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(-r (T-t)) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma \mathrm{d}W(t) \text{
static RandomVariable	AnalyticFormulas.blackScholesGeneralizedOptionValue(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit)	Calculates the Black-Scholes option value of a call, i.e., the payoff max(S(T)-K,0) P, where S follows a log-normal process with constant log-volatility.
static RandomVariable	AnalyticFormulas.blackScholesOptionDelta(RandomVariable initialStockValue, RandomVariable riskFreeRate, RandomVariable volatility, double optionMaturity, double optionStrike)	Calculates the delta of a call option under a Black-Scholes model The method also handles cases where the forward and/or option strike is negative and some limit cases where the forward or the option strike is zero.
static RandomVariable	AnalyticFormulas.blackScholesOptionDelta(RandomVariable initialStockValue, RandomVariable riskFreeRate, RandomVariable volatility, double optionMaturity, RandomVariable optionStrike)	Calculates the delta of a call option under a Black-Scholes model The method also handles cases where the forward and/or option strike is negative and some limit cases where the forward or the option strike is zero.
static RandomVariable	AnalyticFormulas.blackScholesOptionGamma(RandomVariable initialStockValue, RandomVariable riskFreeRate, RandomVariable volatility, double optionMaturity, double optionStrike)	This static method calculated the gamma of a call option under a Black-Scholes model

Methods in net.finmath.functions with parameters of type RandomVariable

Modifier and Type	Method	Description
static RandomVariable	BachelierModel.bachelierHomogeneousOptionDelta(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit)	Calculates the option delta dV(0)/dS(0) of a call option, i.e., the payoff V(T)=max(S(T)-K,0), where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(rt) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma / N(T) \mathrm{d}W(t) \text{
static RandomVariable	BachelierModel.bachelierHomogeneousOptionValue(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit)	Calculates the option value of a call, i.e., the payoff max(S(T)-K,0), where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(rt) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma / N(T) \mathrm{d}W(t) \text{
static RandomVariable	BachelierModel.bachelierHomogeneousOptionVega(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit)	Calculates the vega of a call, i.e., the payoff max(S(T)-K,0) P, where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(rt) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma / N(T) \mathrm{d}W(t) \text{
static RandomVariable	BachelierModel.bachelierInhomogeneousOptionDelta(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit)	Calculates the option delta dV(0)/dS(0) of a call option, i.e., the payoff V(T)=max(S(T)-K,0), where S follows a normal process with constant volatility, i.e., a inhomogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma exp(r (T-t)) \mathrm{d}W(t) \text{
static RandomVariable	BachelierModel.bachelierInhomogeneousOptionValue(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit)	Calculates the option value of a call, i.e., the payoff max(S(T)-K,0), where S follows a normal process with constant volatility, i.e., a inhomogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma exp(r (T-t)) \mathrm{d}W(t) \text{
static RandomVariable	BachelierModel.bachelierInhomogeneousOptionVega(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit)	Calculates the vega of a call, i.e., the payoff max(S(T)-K,0) P, where S follows a normal process with constant volatility, i.e., a Inhomogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp( r t ) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma exp(-r t) \mathrm{d}W(t) \text{
static RandomVariable	BachelierModel.bachelierOptionDelta(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit)	Calculates the option delta dV(0)/dS(0) of a call option, i.e., the payoff V(T)=max(S(T)-K,0), where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(-r (T-t)) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma \mathrm{d}W(t) \text{
static RandomVariable	AnalyticFormulas.bachelierOptionValue(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit)	Calculates the option value of a call, i.e., the payoff max(S(T)-K,0), where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(-r (T-t)) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma \mathrm{d}W(t) \text{
static RandomVariable	BachelierModel.bachelierOptionValue(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit)	Calculates the option value of a call, i.e., the payoff max(S(T)-K,0), where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(-r (T-t)) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma \mathrm{d}W(t) \text{
static RandomVariable	BachelierModel.bachelierOptionVega(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit)	Calculates the vega of a call, i.e., the payoff max(S(T)-K,0) P, where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(-r (T-t)) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma \mathrm{d}W(t) \text{
static RandomVariable	AnalyticFormulas.blackScholesGeneralizedOptionValue(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit)	Calculates the Black-Scholes option value of a call, i.e., the payoff max(S(T)-K,0) P, where S follows a log-normal process with constant log-volatility.
static RandomVariable	AnalyticFormulas.blackScholesOptionDelta(RandomVariable initialStockValue, RandomVariable riskFreeRate, RandomVariable volatility, double optionMaturity, double optionStrike)	Calculates the delta of a call option under a Black-Scholes model The method also handles cases where the forward and/or option strike is negative and some limit cases where the forward or the option strike is zero.
static RandomVariable	AnalyticFormulas.blackScholesOptionDelta(RandomVariable initialStockValue, RandomVariable riskFreeRate, RandomVariable volatility, double optionMaturity, RandomVariable optionStrike)	Calculates the delta of a call option under a Black-Scholes model The method also handles cases where the forward and/or option strike is negative and some limit cases where the forward or the option strike is zero.
static RandomVariable	AnalyticFormulas.blackScholesOptionGamma(RandomVariable initialStockValue, RandomVariable riskFreeRate, RandomVariable volatility, double optionMaturity, double optionStrike)	This static method calculated the gamma of a call option under a Black-Scholes model
double	JarqueBeraTest.test(RandomVariable randomVariable)	Return the test statistic of the Jarque-Bera test for a given random variable.

Uses of RandomVariable in net.finmath.marketdata2.calibration

Methods in net.finmath.marketdata2.calibration that return RandomVariable

Modifier and Type	Method	Description
RandomVariable[]	ParameterAggregation.getParameter()
RandomVariable[]	ParameterObject.getParameter()	Get the current parameter associated with the state of the objects.
RandomVariable[]	ParameterTransformation.getParameter(RandomVariable[] solverParameter)	Return the original parameter for the given (unbounded) solver parameter.
RandomVariable[]	ParameterTransformation.getSolverParameter(RandomVariable[] parameter)	Return the (unbounded) solver parameter for the given original parameter.

Methods in net.finmath.marketdata2.calibration with parameters of type RandomVariable

Modifier and Type	Method	Description
Curve	ParameterAggregation.getCloneForParameter(RandomVariable[] value)
ParameterObject	ParameterObject.getCloneForParameter(RandomVariable[] value)	Create a clone with a modified parameter.
Map<E,RandomVariable[]>	ParameterAggregation.getObjectsToModifyForParameter(RandomVariable[] parameter)
RandomVariable[]	ParameterTransformation.getParameter(RandomVariable[] solverParameter)	Return the original parameter for the given (unbounded) solver parameter.
RandomVariable[]	ParameterTransformation.getSolverParameter(RandomVariable[] parameter)	Return the (unbounded) solver parameter for the given original parameter.
void	ParameterAggregation.setParameter(RandomVariable[] parameter)
void	ParameterObject.setParameter(RandomVariable[] parameter)	Deprecated.

Uses of RandomVariable in net.finmath.marketdata2.interpolation

Methods in net.finmath.marketdata2.interpolation that return RandomVariable

Modifier and Type	Method	Description
RandomVariable	RationalFunctionInterpolation.getValue(double x)	Get an interpolated value for a given argument x.

Constructors in net.finmath.marketdata2.interpolation with parameters of type RandomVariable

Constructor	Description
RationalFunctionInterpolation(double[] points, RandomVariable[] values)	Generate a rational function interpolation from a given set of points.
RationalFunctionInterpolation(double[] points, RandomVariable[] values, RationalFunctionInterpolation.InterpolationMethod interpolationMethod, RationalFunctionInterpolation.ExtrapolationMethod extrapolationMethod)	Generate a rational function interpolation from a given set of points using the specified interpolation and extrapolation method.

Uses of RandomVariable in net.finmath.marketdata2.model

Methods in net.finmath.marketdata2.model that return RandomVariable

Modifier and Type	Method	Description
RandomVariable	AnalyticModel.getRandomVariableForConstant(double value)
RandomVariable	AnalyticModelFromCurvesAndVols.getRandomVariableForConstant(double value)

Uses of RandomVariable in net.finmath.marketdata2.model.curves

Methods in net.finmath.marketdata2.model.curves that return RandomVariable

Modifier and Type	Method	Description
static RandomVariable[]	DiscountCurveInterpolation.createZeroRates(double time, double[] maturities, LIBORModelMonteCarloSimulationModel model)
RandomVariable	DiscountCurveFromForwardCurve.getDiscountFactor(double maturity)
RandomVariable	DiscountCurveFromForwardCurve.getDiscountFactor(AnalyticModel model, double maturity)
RandomVariable	DiscountCurveInterface.getDiscountFactor(double maturity)	Returns the discount factor for the corresponding maturity.
RandomVariable	DiscountCurveInterface.getDiscountFactor(AnalyticModel model, double maturity)	Returns the discount factor for the corresponding maturity.
RandomVariable	DiscountCurveInterpolation.getDiscountFactor(double maturity)
RandomVariable	DiscountCurveInterpolation.getDiscountFactor(AnalyticModel model, double maturity)
RandomVariable	ForwardCurveFromDiscountCurve.getForward(AnalyticModel model, double fixingTime)
RandomVariable	ForwardCurveFromDiscountCurve.getForward(AnalyticModel model, double fixingTime, double paymentOffset)
RandomVariable	ForwardCurveInterface.getForward(AnalyticModel model, double fixingTime)	Returns the forward for the corresponding fixing time.
RandomVariable	ForwardCurveInterface.getForward(AnalyticModel model, double fixingTime, double paymentOffset)	Returns the forward for the corresponding fixing time and paymentOffset.
RandomVariable	ForwardCurveInterpolation.getForward(AnalyticModel model, double fixingTime)
RandomVariable	ForwardCurveInterpolation.getForward(AnalyticModel model, double fixingTime, double paymentOffset)	Returns the forward for the corresponding fixing time.
RandomVariable[]	AbstractForwardCurve.getForwards(AnalyticModel model, double[] fixingTimes)	Returns the forwards for a given vector fixing times.
RandomVariable[]	CurveInterpolation.getParameter()
RandomVariable[]	DiscountCurveFromForwardCurve.getParameter()
RandomVariable[]	ForwardCurveFromDiscountCurve.getParameter()
RandomVariable	AbstractCurve.getValue(double time)
RandomVariable	Curve.getValue(double time)	Returns the value for the time using the interpolation method associated with this curve.
RandomVariable	Curve.getValue(AnalyticModel model, double time)	Returns the value for the time using the interpolation method associated with this curve within a given context, i.e., a model.
RandomVariable	CurveInterpolation.getValue(double time)
RandomVariable	CurveInterpolation.getValue(AnalyticModel model, double time)
RandomVariable	DiscountCurveFromForwardCurve.getValue(AnalyticModel model, double time)
RandomVariable	ForwardCurveFromDiscountCurve.getValue(double time)
RandomVariable	ForwardCurveFromDiscountCurve.getValue(AnalyticModel model, double time)
RandomVariable[]	AbstractCurve.getValues(double[] times)	Return a vector of values corresponding to a given vector of times.
RandomVariable	DiscountCurveInterpolation.getZeroRate(double maturity)	Returns the zero rate for a given maturity, i.e., -ln(df(T)) / T where T is the given maturity and df(T) is the discount factor at time $T$.
RandomVariable[]	DiscountCurveInterpolation.getZeroRates(double[] maturities)	Returns the zero rates for a given vector maturities.

Methods in net.finmath.marketdata2.model.curves with parameters of type RandomVariable

Modifier and Type	Method	Description
protected void	DiscountCurveInterpolation.addDiscountFactor(double maturity, RandomVariable discountFactor, boolean isParameter)
CurveBuilder	CurveBuilder.addPoint(double time, RandomVariable value, boolean isParameter)	Add a point to the curve.
protected void	CurveInterpolation.addPoint(double time, RandomVariable value, boolean isParameter)	Add a point to this curveFromInterpolationPoints.
CurveBuilder	CurveInterpolation.Builder.addPoint(double time, RandomVariable value, boolean isParameter)
protected void	ForwardCurveInterpolation.addPoint(double time, RandomVariable value, boolean isParameter)
static DiscountCurveInterpolation	DiscountCurveInterpolation.createDiscountCurveFromAnnualizedZeroRates(String name, LocalDate referenceDate, double[] times, RandomVariable[] givenAnnualizedZeroRates, boolean[] isParameter, CurveInterpolation.InterpolationMethod interpolationMethod, CurveInterpolation.ExtrapolationMethod extrapolationMethod, CurveInterpolation.InterpolationEntity interpolationEntity)	Create a discount curve from given times and given annualized zero rates using given interpolation and extrapolation methods.
static DiscountCurveInterpolation	DiscountCurveInterpolation.createDiscountCurveFromAnnualizedZeroRates(String name, LocalDate referenceDate, double[] times, RandomVariable[] givenAnnualizedZeroRates, CurveInterpolation.InterpolationMethod interpolationMethod, CurveInterpolation.ExtrapolationMethod extrapolationMethod, CurveInterpolation.InterpolationEntity interpolationEntity)	Create a discount curve from given times and given annualized zero rates using given interpolation and extrapolation methods.
static DiscountCurveInterpolation	DiscountCurveInterpolation.createDiscountCurveFromDiscountFactors(String name, double[] times, RandomVariable[] givenDiscountFactors)	Create a discount curve from given times and given discount factors using default interpolation and extrapolation methods.
static DiscountCurveInterpolation	DiscountCurveInterpolation.createDiscountCurveFromDiscountFactors(String name, double[] times, RandomVariable[] givenDiscountFactors, boolean[] isParameter, CurveInterpolation.InterpolationMethod interpolationMethod, CurveInterpolation.ExtrapolationMethod extrapolationMethod, CurveInterpolation.InterpolationEntity interpolationEntity)	Create a discount curve from given times and given discount factors using given interpolation and extrapolation methods.
static DiscountCurveInterpolation	DiscountCurveInterpolation.createDiscountCurveFromDiscountFactors(String name, double[] times, RandomVariable[] givenDiscountFactors, CurveInterpolation.InterpolationMethod interpolationMethod, CurveInterpolation.ExtrapolationMethod extrapolationMethod, CurveInterpolation.InterpolationEntity interpolationEntity)	Create a discount curve from given times and given discount factors using given interpolation and extrapolation methods.
static DiscountCurveInterpolation	DiscountCurveInterpolation.createDiscountCurveFromDiscountFactors(String name, LocalDate referenceDate, double[] times, RandomVariable[] givenDiscountFactors, boolean[] isParameter, CurveInterpolation.InterpolationMethod interpolationMethod, CurveInterpolation.ExtrapolationMethod extrapolationMethod, CurveInterpolation.InterpolationEntity interpolationEntity)	Create a discount curve from given times and given discount factors using given interpolation and extrapolation methods.
static DiscountCurveInterpolation	DiscountCurveInterpolation.createDiscountCurveFromZeroRates(String name, double[] times, RandomVariable[] givenZeroRates)	Create a discount curve from given times and given zero rates using default interpolation and extrapolation methods.
static DiscountCurveInterpolation	DiscountCurveInterpolation.createDiscountCurveFromZeroRates(String name, LocalDate referenceDate, double[] times, RandomVariable[] givenZeroRates, boolean[] isParameter, CurveInterpolation.InterpolationMethod interpolationMethod, CurveInterpolation.ExtrapolationMethod extrapolationMethod, CurveInterpolation.InterpolationEntity interpolationEntity)	Create a discount curve from given times and given zero rates using given interpolation and extrapolation methods.
static DiscountCurveInterpolation	DiscountCurveInterpolation.createDiscountCurveFromZeroRates(String name, LocalDate referenceDate, double[] times, RandomVariable[] givenZeroRates, CurveInterpolation.InterpolationMethod interpolationMethod, CurveInterpolation.ExtrapolationMethod extrapolationMethod, CurveInterpolation.InterpolationEntity interpolationEntity)	Create a discount curve from given times and given zero rates using given interpolation and extrapolation methods.
static DiscountCurveInterpolation	DiscountCurveInterpolation.createDiscountCurveFromZeroRates(String name, Date referenceDate, double[] times, RandomVariable[] givenZeroRates, boolean[] isParameter, CurveInterpolation.InterpolationMethod interpolationMethod, CurveInterpolation.ExtrapolationMethod extrapolationMethod, CurveInterpolation.InterpolationEntity interpolationEntity)	Create a discount curve from given times and given zero rates using given interpolation and extrapolation methods.
static DiscountCurveInterface	DiscountCurveInterpolation.createDiscountFactorsFromForwardRates(String name, TimeDiscretization tenor, RandomVariable[] forwardRates)	Create a discount curve from given time discretization and forward rates.
static ForwardCurveInterpolation	ForwardCurveInterpolation.createForwardCurveFromDiscountFactors(String name, double[] times, RandomVariable[] givenDiscountFactors, double paymentOffset)	Create a forward curve from given times and discount factors.
static ForwardCurveInterpolation	ForwardCurveInterpolation.createForwardCurveFromForwards(String name, double[] times, RandomVariable[] givenForwards, double paymentOffset)	Create a forward curve from given times and given forwards.
static ForwardCurveInterpolation	ForwardCurveInterpolation.createForwardCurveFromForwards(String name, double[] times, RandomVariable[] givenForwards, AnalyticModel model, String discountCurveName, double paymentOffset)	Create a forward curve from given times and given forwards with respect to an associated discount curve and payment offset.
static ForwardCurveInterpolation	ForwardCurveInterpolation.createForwardCurveFromForwards(String name, LocalDate referenceDate, String paymentOffsetCode, String interpolationEntityForward, String discountCurveName, AnalyticModel model, double[] times, RandomVariable[] givenForwards)	Create a forward curve from given times and given forwards.
static ForwardCurveInterpolation	ForwardCurveInterpolation.createForwardCurveFromForwards(String name, LocalDate referenceDate, String paymentOffsetCode, ForwardCurveInterpolation.InterpolationEntityForward interpolationEntityForward, String discountCurveName, AnalyticModel model, double[] times, RandomVariable[] givenForwards)	Create a forward curve from given times and given forwards.
static ForwardCurveInterpolation	ForwardCurveInterpolation.createForwardCurveFromForwards(String name, LocalDate referenceDate, String paymentOffsetCode, BusinessdayCalendar paymentBusinessdayCalendar, BusinessdayCalendar.DateRollConvention paymentDateRollConvention, CurveInterpolation.InterpolationMethod interpolationMethod, CurveInterpolation.ExtrapolationMethod extrapolationMethod, CurveInterpolation.InterpolationEntity interpolationEntity, ForwardCurveInterpolation.InterpolationEntityForward interpolationEntityForward, String discountCurveName, AnalyticModel model, double[] times, RandomVariable[] givenForwards)	Create a forward curve from given times and given forwards.
static ForwardCurveInterpolation	ForwardCurveInterpolation.createForwardCurveFromForwards(String name, Date referenceDate, String paymentOffsetCode, BusinessdayCalendar paymentBusinessdayCalendar, BusinessdayCalendar.DateRollConvention paymentDateRollConvention, CurveInterpolation.InterpolationMethod interpolationMethod, CurveInterpolation.ExtrapolationMethod extrapolationMethod, CurveInterpolation.InterpolationEntity interpolationEntity, ForwardCurveInterpolation.InterpolationEntityForward interpolationEntityForward, String discountCurveName, AnalyticModel model, double[] times, RandomVariable[] givenForwards)	Create a forward curve from given times and given forwards.
Curve	AbstractCurve.getCloneForParameter(RandomVariable[] value)
Curve	Curve.getCloneForParameter(RandomVariable[] value)
Curve	CurveInterpolation.getCloneForParameter(RandomVariable[] parameter)
void	CurveInterpolation.setParameter(RandomVariable[] parameter)
void	DiscountCurveFromForwardCurve.setParameter(RandomVariable[] parameter)

Constructors in net.finmath.marketdata2.model.curves with parameters of type RandomVariable

Constructor	Description
CurveInterpolation(String name, LocalDate referenceDate, CurveInterpolation.InterpolationMethod interpolationMethod, CurveInterpolation.ExtrapolationMethod extrapolationMethod, CurveInterpolation.InterpolationEntity interpolationEntity, double[] times, RandomVariable[] values)	Create a curveFromInterpolationPoints with a given name, reference date and an interpolation method from given points

Uses of RandomVariable in net.finmath.marketdata2.products

Methods in net.finmath.marketdata2.products that return RandomVariable

Modifier and Type	Method	Description
static RandomVariable	Swap.getForwardSwapRate(Schedule fixSchedule, Schedule floatSchedule, ForwardCurveInterface forwardCurve)
static RandomVariable	Swap.getForwardSwapRate(Schedule fixSchedule, Schedule floatSchedule, ForwardCurveInterface forwardCurve, AnalyticModel model)
static RandomVariable	Swap.getForwardSwapRate(TimeDiscretization fixTenor, TimeDiscretization floatTenor, ForwardCurveInterface forwardCurve)
static RandomVariable	Swap.getForwardSwapRate(TimeDiscretization fixTenor, TimeDiscretization floatTenor, ForwardCurveInterface forwardCurve, DiscountCurveInterface discountCurve)
RandomVariable	Deposit.getRate(AnalyticModel model)	Return the deposit rate implied by the given model's curve.
RandomVariable	ForwardRateAgreement.getRate(AnalyticModel model)	Return the par FRA rate for a given curve.
static RandomVariable	SwapAnnuity.getSwapAnnuity(double evaluationTime, Schedule schedule, DiscountCurveInterface discountCurve, AnalyticModel model)	Function to calculate an (idealized) swap annuity for a given schedule and discount curve.
static RandomVariable	SwapAnnuity.getSwapAnnuity(Schedule schedule, DiscountCurveInterface discountCurve)	Function to calculate an (idealized) swap annuity for a given schedule and discount curve.
static RandomVariable	SwapAnnuity.getSwapAnnuity(Schedule schedule, ForwardCurveInterface forwardCurve)	Function to calculate an (idealized) single curve swap annuity for a given schedule and forward curve.
static RandomVariable	SwapAnnuity.getSwapAnnuity(TimeDiscretization tenor, DiscountCurveInterface discountCurve)	Function to calculate an (idealized) swap annuity for a given schedule and discount curve.
static RandomVariable	SwapAnnuity.getSwapAnnuity(TimeDiscretization tenor, ForwardCurveInterface forwardCurve)	Function to calculate an (idealized) single curve swap annuity for a given schedule and forward curve.
RandomVariable	AbstractAnalyticProduct.getValue(AnalyticModel model)
RandomVariable	AnalyticProduct.getValue(double evaluationTime, AnalyticModel model)	Return the valuation of the product using the given model.
RandomVariable	Cashflow.getValue(double evaluationTime, AnalyticModel model)
RandomVariable	Deposit.getValue(double evaluationTime, AnalyticModel model)
RandomVariable	Forward.getValue(double evaluationTime, AnalyticModel model)
RandomVariable	ForwardRateAgreement.getValue(double evaluationTime, AnalyticModel model)
RandomVariable	MarketForwardRateAgreement.getValue(double evaluationTime, AnalyticModel model)
RandomVariable	Performance.getValue(double evaluationTime, AnalyticModel model)
RandomVariable	Portfolio.getValue(double evaluationTime, AnalyticModel model)
RandomVariable	Swap.getValue(double evaluationTime, AnalyticModel model)
RandomVariable	SwapAnnuity.getValue(double evaluationTime, AnalyticModel model)
RandomVariable	SwapLeg.getValue(double evaluationTime, AnalyticModel model)

Uses of RandomVariable in net.finmath.modelling.productfactory

Methods in net.finmath.modelling.productfactory that return RandomVariable

Modifier and Type	Method	Description
RandomVariable	InterestRateMonteCarloProductFactory.SwapMonteCarlo.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	InterestRateMonteCarloProductFactory.SwaptionPhysicalMonteCarlo.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)

Uses of RandomVariable in net.finmath.montecarlo

Classes in net.finmath.montecarlo that implement RandomVariable

Modifier and Type	Class	Description
class	RandomVariableFromDoubleArray	The class RandomVariableFromDoubleArray represents a random variable being the evaluation of a stochastic process at a certain time within a Monte-Carlo simulation.
class	RandomVariableFromFloatArray	The class RandomVariableFromFloatArray represents a random variable being the evaluation of a stochastic process at a certain time within a Monte-Carlo simulation.
class	RandomVariableLazyEvaluation	Implements a Monte-Carlo random variable (like RandomVariableFromDoubleArray using late evaluation of Java 8 streams Accesses performed exclusively through the interface RandomVariable is thread safe (and does not mutate the class).

Methods in net.finmath.montecarlo that return RandomVariable

Modifier and Type	Method	Description
RandomVariable	RandomVariableFromDoubleArray.abs()
RandomVariable	RandomVariableFromFloatArray.abs()
RandomVariable	RandomVariableLazyEvaluation.abs()
RandomVariable	RandomVariableFromDoubleArray.accrue(RandomVariable rate, double periodLength)
RandomVariable	RandomVariableFromFloatArray.accrue(RandomVariable rate, double periodLength)
RandomVariable	RandomVariableLazyEvaluation.accrue(RandomVariable rate, double periodLength)
RandomVariable	RandomVariableFromDoubleArray.add(double value)
RandomVariable	RandomVariableFromDoubleArray.add(RandomVariable randomVariable)
RandomVariable	RandomVariableFromFloatArray.add(double value)
RandomVariable	RandomVariableFromFloatArray.add(RandomVariable randomVariable)
RandomVariable	RandomVariableLazyEvaluation.add(double value)
RandomVariable	RandomVariableLazyEvaluation.add(RandomVariable randomVariable)
RandomVariable	RandomVariableFromDoubleArray.addProduct(RandomVariable factor1, double factor2)
RandomVariable	RandomVariableFromDoubleArray.addProduct(RandomVariable factor1, RandomVariable factor2)
RandomVariable	RandomVariableFromFloatArray.addProduct(RandomVariable factor1, double factor2)
RandomVariable	RandomVariableFromFloatArray.addProduct(RandomVariable factor1, RandomVariable factor2)
RandomVariable	RandomVariableLazyEvaluation.addProduct(RandomVariable factor1, double factor2)
RandomVariable	RandomVariableLazyEvaluation.addProduct(RandomVariable factor1, RandomVariable factor2)
RandomVariable	RandomVariableFromDoubleArray.addRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	RandomVariableFromFloatArray.addRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	RandomVariableLazyEvaluation.addRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	RandomVariableFromDoubleArray.addSumProduct(List<RandomVariable> factor1, List<RandomVariable> factor2)
RandomVariable	RandomVariableFromFloatArray.addSumProduct(List<RandomVariable> factor1, List<RandomVariable> factor2)
RandomVariable	RandomVariableFromDoubleArray.apply(DoubleBinaryOperator operatorOuter, DoubleBinaryOperator operatorInner, RandomVariable argument1, RandomVariable argument2)
RandomVariable	RandomVariableFromDoubleArray.apply(DoubleBinaryOperator operator, RandomVariable argument)
RandomVariable	RandomVariableFromDoubleArray.apply(DoubleUnaryOperator operator)
RandomVariable	RandomVariableFromDoubleArray.apply(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2)
RandomVariable	RandomVariableFromFloatArray.apply(DoubleBinaryOperator operator, RandomVariable argument)
RandomVariable	RandomVariableFromFloatArray.apply(DoubleUnaryOperator operator)
RandomVariable	RandomVariableFromFloatArray.apply(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2)
RandomVariable	RandomVariableLazyEvaluation.apply(DoubleBinaryOperator operatorOuter, DoubleBinaryOperator operatorInner, RandomVariable argument1, RandomVariable argument2)
RandomVariable	RandomVariableLazyEvaluation.apply(DoubleBinaryOperator operator, RandomVariable argument)
RandomVariable	RandomVariableLazyEvaluation.apply(DoubleUnaryOperator operator)
RandomVariable	RandomVariableLazyEvaluation.apply(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2)
RandomVariable	RandomVariableFromDoubleArray.average()
RandomVariable	RandomVariableFromFloatArray.average()
RandomVariable	RandomVariableLazyEvaluation.average()
RandomVariable	RandomVariableFromDoubleArray.bus(double value)
RandomVariable	RandomVariableFromDoubleArray.bus(RandomVariable randomVariable)
RandomVariable	RandomVariableFromFloatArray.bus(RandomVariable randomVariable)
RandomVariable	RandomVariableLazyEvaluation.bus(RandomVariable randomVariable)
RandomVariable	RandomVariableFromDoubleArray.cache()
RandomVariable	RandomVariableFromFloatArray.cache()
RandomVariable	RandomVariableLazyEvaluation.cache()
RandomVariable	RandomVariableFromDoubleArray.cap(double cap)
RandomVariable	RandomVariableFromDoubleArray.cap(RandomVariable randomVariable)
RandomVariable	RandomVariableFromFloatArray.cap(double cap)
RandomVariable	RandomVariableFromFloatArray.cap(RandomVariable randomVariable)
RandomVariable	RandomVariableLazyEvaluation.cap(double cap)
RandomVariable	RandomVariableLazyEvaluation.cap(RandomVariable cap)
RandomVariable	RandomVariableFromDoubleArray.choose(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative)
RandomVariable	RandomVariableFromFloatArray.choose(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative)
RandomVariable	RandomVariableLazyEvaluation.choose(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative)
RandomVariable	RandomVariableFromDoubleArray.cos()
RandomVariable	RandomVariableFromFloatArray.cos()
RandomVariable	RandomVariableLazyEvaluation.cos()
RandomVariable	AbstractRandomVariableFactory.createRandomVariable(double value)
abstract RandomVariable	AbstractRandomVariableFactory.createRandomVariable(double time, double value)
abstract RandomVariable	AbstractRandomVariableFactory.createRandomVariable(double time, double[] values)
RandomVariable	RandomVariableFactory.createRandomVariable(double value)	Create a (deterministic) random variable from a constant.
RandomVariable	RandomVariableFactory.createRandomVariable(double time, double value)	Create a (deterministic) random variable from a constant using a specific filtration time.
RandomVariable	RandomVariableFactory.createRandomVariable(double time, double[] values)	Create a random variable from an array using a specific filtration time.
RandomVariable	RandomVariableFloatFactory.createRandomVariable(double time, double value)
RandomVariable	RandomVariableFloatFactory.createRandomVariable(double time, double[] values)
RandomVariable	RandomVariableFromArrayFactory.createRandomVariable(double value)
RandomVariable	RandomVariableFromArrayFactory.createRandomVariable(double time, double value)
RandomVariable	RandomVariableFromArrayFactory.createRandomVariable(double time, double[] values)
RandomVariable	RandomVariableLazyEvaluationFactory.createRandomVariable(double time, double value)
RandomVariable	RandomVariableLazyEvaluationFactory.createRandomVariable(double time, double[] values)
RandomVariable[]	AbstractRandomVariableFactory.createRandomVariableArray(double[] values)
RandomVariable[]	RandomVariableFactory.createRandomVariableArray(double[] values)	Create an array of (deterministic) random variables from an array of constants.
RandomVariable[][]	AbstractRandomVariableFactory.createRandomVariableMatrix(double[][] values)
RandomVariable[][]	RandomVariableFactory.createRandomVariableMatrix(double[][] values)	Create a matrix of (deterministic) random variables from an matrix of constants.
RandomVariable	RandomVariableFromDoubleArray.discount(RandomVariable rate, double periodLength)
RandomVariable	RandomVariableFromFloatArray.discount(RandomVariable rate, double periodLength)
RandomVariable	RandomVariableLazyEvaluation.discount(RandomVariable rate, double periodLength)
RandomVariable	RandomVariableFromDoubleArray.div(double value)
RandomVariable	RandomVariableFromDoubleArray.div(RandomVariable randomVariable)
RandomVariable	RandomVariableFromFloatArray.div(double value)
RandomVariable	RandomVariableFromFloatArray.div(RandomVariable randomVariable)
RandomVariable	RandomVariableLazyEvaluation.div(double value)
RandomVariable	RandomVariableLazyEvaluation.div(RandomVariable randomVariable)
RandomVariable	RandomVariableLazyEvaluation.exp()
RandomVariable	RandomVariableLazyEvaluation.expand(int numberOfPaths)
RandomVariable	RandomVariableFromDoubleArray.floor(double floor)
RandomVariable	RandomVariableFromDoubleArray.floor(RandomVariable randomVariable)
RandomVariable	RandomVariableFromFloatArray.floor(double floor)
RandomVariable	RandomVariableFromFloatArray.floor(RandomVariable randomVariable)
RandomVariable	RandomVariableLazyEvaluation.floor(double floor)
RandomVariable	RandomVariableLazyEvaluation.floor(RandomVariable floor)
RandomVariable	BrownianBridge.getBrownianIncrement(int timeIndex, int factor)
default RandomVariable	BrownianMotion.getBrownianIncrement(double time, int factor)	Return the Brownian increment for a given timeIndex.
RandomVariable	BrownianMotion.getBrownianIncrement(int timeIndex, int factor)	Return the Brownian increment for a given timeIndex.
RandomVariable	BrownianMotionFromMersenneRandomNumbers.getBrownianIncrement(int timeIndex, int factor)
RandomVariable	BrownianMotionFromRandomNumberGenerator.getBrownianIncrement(int timeIndex, int factor)
RandomVariable	BrownianMotionView.getBrownianIncrement(int timeIndex, int factor)
RandomVariable	BrownianMotionWithControlVariate.getBrownianIncrement(int timeIndex, int factorIndex)
RandomVariable	CorrelatedBrownianMotion.getBrownianIncrement(int timeIndex, int factor)
RandomVariable	RandomVariableFromDoubleArray.getConditionalExpectation(ConditionalExpectationEstimator conditionalExpectationOperator)
RandomVariable	RandomVariableFromFloatArray.getConditionalExpectation(ConditionalExpectationEstimator conditionalExpectationOperator)
RandomVariable[]	BrownianBridge.getIncrement(int timeIndex)
RandomVariable	BrownianBridge.getIncrement(int timeIndex, int factor)
RandomVariable	BrownianMotionFromMersenneRandomNumbers.getIncrement(int timeIndex, int factor)
RandomVariable	BrownianMotionFromRandomNumberGenerator.getIncrement(int timeIndex, int factor)
RandomVariable	BrownianMotionView.getIncrement(int timeIndex, int factor)
RandomVariable	BrownianMotionWithControlVariate.getIncrement(int timeIndex, int factor)
RandomVariable	CorrelatedBrownianMotion.getIncrement(int timeIndex, int factor)
RandomVariable	GammaProcess.getIncrement(int timeIndex, int factor)
default RandomVariable[]	IndependentIncrements.getIncrement(int timeIndex)	Return the increment for a given timeIndex.
RandomVariable	IndependentIncrements.getIncrement(int timeIndex, int factor)	Return the increment for a given timeIndex and given factor.
RandomVariable	IndependentIncrementsFromICDF.getIncrement(int timeIndex, int factor)
RandomVariable	JumpProcessIncrements.getIncrement(int timeIndex, int factor)
RandomVariable	MertonJumpProcess.getIncrement(int timeIndex, int factor)
RandomVariable	VarianceGammaProcess.getIncrement(int timeIndex, int factor)
RandomVariable	MonteCarloSimulationModel.getMonteCarloWeights(double time)	This method returns the weights of a weighted Monte Carlo method (the probability density).
RandomVariable	MonteCarloSimulationModel.getMonteCarloWeights(int timeIndex)	This method returns the weights of a weighted Monte Carlo method (the probability density).
RandomVariable	BrownianBridge.getRandomVariableForConstant(double value)
RandomVariable	BrownianMotion.getRandomVariableForConstant(double value)	Returns a random variable which is initialized to a constant, but has exactly the same number of paths or discretization points as the ones used by this BrownianMotion.
RandomVariable	BrownianMotionFromMersenneRandomNumbers.getRandomVariableForConstant(double value)
RandomVariable	BrownianMotionFromRandomNumberGenerator.getRandomVariableForConstant(double value)
RandomVariable	BrownianMotionView.getRandomVariableForConstant(double value)
RandomVariable	BrownianMotionWithControlVariate.getRandomVariableForConstant(double value)
RandomVariable	CorrelatedBrownianMotion.getRandomVariableForConstant(double value)
RandomVariable	GammaProcess.getRandomVariableForConstant(double value)
RandomVariable	IndependentIncrements.getRandomVariableForConstant(double value)	Returns a random variable which is initialized to a constant, but has exactly the same number of paths or discretization points as the ones used by this BrownianMotion.
RandomVariable	IndependentIncrementsFromICDF.getRandomVariableForConstant(double value)
RandomVariable	JumpProcessIncrements.getRandomVariableForConstant(double value)
RandomVariable	MertonJumpProcess.getRandomVariableForConstant(double value)
RandomVariable	MonteCarloSimulationModel.getRandomVariableForConstant(double value)	Returns a random variable which is initialized to a constant, but has exactly the same number of paths or discretization points as the ones used by this MonteCarloSimulationModel.
RandomVariable	VarianceGammaProcess.getRandomVariableForConstant(double value)
static RandomVariable	RandomVariableFactory.getRandomVariableOrDefault(RandomVariableFactory randomVariableFactory, Object value, RandomVariable defaultValue)	Static method for creating random variables from Objects.
abstract RandomVariable	AbstractMonteCarloProduct.getValue(double evaluationTime, MonteCarloSimulationModel model)
RandomVariable	MonteCarloProduct.getValue(double evaluationTime, MonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	RandomVariableFromDoubleArray.invert()
RandomVariable	RandomVariableFromFloatArray.invert()
RandomVariable	RandomVariableLazyEvaluation.invert()
RandomVariable	RandomVariableFromDoubleArray.isNaN()
RandomVariable	RandomVariableFromFloatArray.isNaN()
RandomVariable	RandomVariableLazyEvaluation.isNaN()
RandomVariable	RandomVariableLazyEvaluation.log()
RandomVariable	RandomVariableFromDoubleArray.mult(double value)
RandomVariable	RandomVariableFromDoubleArray.mult(RandomVariable randomVariable)
RandomVariable	RandomVariableFromFloatArray.mult(double value)
RandomVariable	RandomVariableFromFloatArray.mult(RandomVariable randomVariable)
RandomVariable	RandomVariableLazyEvaluation.mult(double value)
RandomVariable	RandomVariableLazyEvaluation.mult(RandomVariable randomVariable)
RandomVariable	RandomVariableFromDoubleArray.pow(double exponent)
RandomVariable	RandomVariableFromFloatArray.pow(double exponent)
RandomVariable	RandomVariableLazyEvaluation.pow(double exponent)
RandomVariable	RandomVariableFromDoubleArray.sin()
RandomVariable	RandomVariableFromFloatArray.sin()
RandomVariable	RandomVariableLazyEvaluation.sin()
RandomVariable	RandomVariableFromDoubleArray.sqrt()
RandomVariable	RandomVariableFromFloatArray.sqrt()
RandomVariable	RandomVariableLazyEvaluation.sqrt()
RandomVariable	RandomVariableFromDoubleArray.squared()
RandomVariable	RandomVariableFromFloatArray.squared()
RandomVariable	RandomVariableLazyEvaluation.squared()
RandomVariable	RandomVariableFromDoubleArray.sub(double value)
RandomVariable	RandomVariableFromDoubleArray.sub(RandomVariable randomVariable)
RandomVariable	RandomVariableFromFloatArray.sub(double value)
RandomVariable	RandomVariableFromFloatArray.sub(RandomVariable randomVariable)
RandomVariable	RandomVariableLazyEvaluation.sub(double value)
RandomVariable	RandomVariableLazyEvaluation.sub(RandomVariable randomVariable)
RandomVariable	RandomVariableFromDoubleArray.subRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	RandomVariableFromFloatArray.subRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	RandomVariableLazyEvaluation.subRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	RandomVariableFromDoubleArray.vid(double value)
RandomVariable	RandomVariableFromDoubleArray.vid(RandomVariable randomVariable)
RandomVariable	RandomVariableFromFloatArray.vid(RandomVariable randomVariable)
RandomVariable	RandomVariableLazyEvaluation.vid(RandomVariable randomVariable)

Methods in net.finmath.montecarlo with parameters of type RandomVariable

Modifier and Type	Method	Description
RandomVariable	RandomVariableFromDoubleArray.accrue(RandomVariable rate, double periodLength)
RandomVariable	RandomVariableFromFloatArray.accrue(RandomVariable rate, double periodLength)
RandomVariable	RandomVariableLazyEvaluation.accrue(RandomVariable rate, double periodLength)
RandomVariable	RandomVariableFromDoubleArray.add(RandomVariable randomVariable)
RandomVariable	RandomVariableFromFloatArray.add(RandomVariable randomVariable)
RandomVariable	RandomVariableLazyEvaluation.add(RandomVariable randomVariable)
RandomVariable	RandomVariableFromDoubleArray.addProduct(RandomVariable factor1, double factor2)
RandomVariable	RandomVariableFromDoubleArray.addProduct(RandomVariable factor1, RandomVariable factor2)
RandomVariable	RandomVariableFromFloatArray.addProduct(RandomVariable factor1, double factor2)
RandomVariable	RandomVariableFromFloatArray.addProduct(RandomVariable factor1, RandomVariable factor2)
RandomVariable	RandomVariableLazyEvaluation.addProduct(RandomVariable factor1, double factor2)
RandomVariable	RandomVariableLazyEvaluation.addProduct(RandomVariable factor1, RandomVariable factor2)
RandomVariable	RandomVariableFromDoubleArray.addRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	RandomVariableFromFloatArray.addRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	RandomVariableLazyEvaluation.addRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	RandomVariableFromDoubleArray.apply(DoubleBinaryOperator operatorOuter, DoubleBinaryOperator operatorInner, RandomVariable argument1, RandomVariable argument2)
RandomVariable	RandomVariableFromDoubleArray.apply(DoubleBinaryOperator operator, RandomVariable argument)
RandomVariable	RandomVariableFromDoubleArray.apply(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2)
RandomVariable	RandomVariableFromFloatArray.apply(DoubleBinaryOperator operator, RandomVariable argument)
RandomVariable	RandomVariableFromFloatArray.apply(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2)
RandomVariable	RandomVariableLazyEvaluation.apply(DoubleBinaryOperator operatorOuter, DoubleBinaryOperator operatorInner, RandomVariable argument1, RandomVariable argument2)
RandomVariable	RandomVariableLazyEvaluation.apply(DoubleBinaryOperator operator, RandomVariable argument)
RandomVariable	RandomVariableLazyEvaluation.apply(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2)
RandomVariable	RandomVariableFromDoubleArray.bus(RandomVariable randomVariable)
RandomVariable	RandomVariableFromFloatArray.bus(RandomVariable randomVariable)
RandomVariable	RandomVariableLazyEvaluation.bus(RandomVariable randomVariable)
RandomVariable	RandomVariableFromDoubleArray.cap(RandomVariable randomVariable)
RandomVariable	RandomVariableFromFloatArray.cap(RandomVariable randomVariable)
RandomVariable	RandomVariableLazyEvaluation.cap(RandomVariable cap)
RandomVariable	RandomVariableFromDoubleArray.choose(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative)
RandomVariable	RandomVariableFromFloatArray.choose(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative)
RandomVariable	RandomVariableLazyEvaluation.choose(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative)
RandomVariable	RandomVariableFromDoubleArray.discount(RandomVariable rate, double periodLength)
RandomVariable	RandomVariableFromFloatArray.discount(RandomVariable rate, double periodLength)
RandomVariable	RandomVariableLazyEvaluation.discount(RandomVariable rate, double periodLength)
RandomVariable	RandomVariableFromDoubleArray.div(RandomVariable randomVariable)
RandomVariable	RandomVariableFromFloatArray.div(RandomVariable randomVariable)
RandomVariable	RandomVariableLazyEvaluation.div(RandomVariable randomVariable)
boolean	RandomVariableFromDoubleArray.equals(RandomVariable randomVariable)
boolean	RandomVariableFromFloatArray.equals(RandomVariable randomVariable)
boolean	RandomVariableLazyEvaluation.equals(RandomVariable randomVariable)
RandomVariable	RandomVariableFromDoubleArray.floor(RandomVariable randomVariable)
RandomVariable	RandomVariableFromFloatArray.floor(RandomVariable randomVariable)
RandomVariable	RandomVariableLazyEvaluation.floor(RandomVariable floor)
double	RandomVariableFromDoubleArray.getAverage(RandomVariable probabilities)
double	RandomVariableFromFloatArray.getAverage(RandomVariable probabilities)
double	RandomVariableLazyEvaluation.getAverage(RandomVariable probabilities)
double	RandomVariableFromDoubleArray.getQuantile(double quantile, RandomVariable probabilities)
double	RandomVariableFromFloatArray.getQuantile(double quantile, RandomVariable probabilities)
double	RandomVariableLazyEvaluation.getQuantile(double quantile, RandomVariable probabilities)
static RandomVariable	RandomVariableFactory.getRandomVariableOrDefault(RandomVariableFactory randomVariableFactory, Object value, RandomVariable defaultValue)	Static method for creating random variables from Objects.
double	RandomVariableFromDoubleArray.getStandardDeviation(RandomVariable probabilities)
double	RandomVariableFromFloatArray.getStandardDeviation(RandomVariable probabilities)
double	RandomVariableLazyEvaluation.getStandardDeviation(RandomVariable probabilities)
double	RandomVariableFromDoubleArray.getStandardError(RandomVariable probabilities)
double	RandomVariableFromFloatArray.getStandardError(RandomVariable probabilities)
double	RandomVariableLazyEvaluation.getStandardError(RandomVariable probabilities)
double	RandomVariableFromDoubleArray.getVariance(RandomVariable probabilities)
double	RandomVariableFromFloatArray.getVariance(RandomVariable probabilities)
double	RandomVariableLazyEvaluation.getVariance(RandomVariable probabilities)
RandomVariable	RandomVariableFromDoubleArray.mult(RandomVariable randomVariable)
RandomVariable	RandomVariableFromFloatArray.mult(RandomVariable randomVariable)
RandomVariable	RandomVariableLazyEvaluation.mult(RandomVariable randomVariable)
RandomVariable	RandomVariableFromDoubleArray.sub(RandomVariable randomVariable)
RandomVariable	RandomVariableFromFloatArray.sub(RandomVariable randomVariable)
RandomVariable	RandomVariableLazyEvaluation.sub(RandomVariable randomVariable)
RandomVariable	RandomVariableFromDoubleArray.subRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	RandomVariableFromFloatArray.subRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	RandomVariableLazyEvaluation.subRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	RandomVariableFromDoubleArray.vid(RandomVariable randomVariable)
RandomVariable	RandomVariableFromFloatArray.vid(RandomVariable randomVariable)
RandomVariable	RandomVariableLazyEvaluation.vid(RandomVariable randomVariable)

Method parameters in net.finmath.montecarlo with type arguments of type RandomVariable

Modifier and Type	Method	Description
RandomVariable	RandomVariableFromDoubleArray.addSumProduct(List<RandomVariable> factor1, List<RandomVariable> factor2)
RandomVariable	RandomVariableFromFloatArray.addSumProduct(List<RandomVariable> factor1, List<RandomVariable> factor2)

Constructors in net.finmath.montecarlo with parameters of type RandomVariable

Constructor	Description
BrownianBridge(TimeDiscretization timeDiscretization, int numberOfPaths, int seed, RandomVariable[] start, RandomVariable[] end)	Construct a Brownian bridge, bridging from a given start to a given end.
BrownianBridge(TimeDiscretization timeDiscretization, int numberOfPaths, int seed, RandomVariable start, RandomVariable end)	Construct a Brownian bridge, bridging from a given start to a given end.
RandomVariableFromDoubleArray(RandomVariable value)	Create a random variable from a given other implementation of RandomVariable.
RandomVariableFromDoubleArray(RandomVariable value, DoubleUnaryOperator function)	Create a random variable by applying a function to a given other implementation of RandomVariable.
RandomVariableFromFloatArray(RandomVariable value)	Create a random variable from a given other implementation of RandomVariable.
RandomVariableFromFloatArray(RandomVariable value, DoubleUnaryOperator function)	Create a random variable by applying a function to a given other implementation of RandomVariable.
RandomVariableLazyEvaluation(RandomVariable value)	Create a random variable from a given other implementation of RandomVariable.
RandomVariableLazyEvaluation(RandomVariable value, DoubleUnaryOperator function)	Create a random variable by applying a function to a given other implementation of RandomVariable.

Uses of RandomVariable in net.finmath.montecarlo.assetderivativevaluation

Methods in net.finmath.montecarlo.assetderivativevaluation that return RandomVariable

Modifier and Type	Method	Description
RandomVariable	MonteCarloMultiAssetBlackScholesModel.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	MonteCarloMultiAssetBlackScholesModel.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	AssetModelMonteCarloSimulationModel.getAssetValue(double time, int assetIndex)	Returns the random variable representing the asset's value at a given time for a given asset.
RandomVariable	AssetModelMonteCarloSimulationModel.getAssetValue(int timeIndex, int assetIndex)	Returns the random variable representing the asset's value at a given time for a given asset.
RandomVariable	MonteCarloAssetModel.getAssetValue(double time, int assetIndex)
RandomVariable	MonteCarloAssetModel.getAssetValue(int timeIndex, int assetIndex)
RandomVariable	MonteCarloBlackScholesModel.getAssetValue(double time, int assetIndex)
RandomVariable	MonteCarloBlackScholesModel.getAssetValue(int timeIndex, int assetIndex)
RandomVariable	MonteCarloMertonModel.getAssetValue(double time, int assetIndex)
RandomVariable	MonteCarloMertonModel.getAssetValue(int timeIndex, int assetIndex)
RandomVariable	MonteCarloMultiAssetBlackScholesModel.getAssetValue(double time, int assetIndex)
RandomVariable	MonteCarloMultiAssetBlackScholesModel.getAssetValue(int timeIndex, int assetIndex)
RandomVariable	MonteCarloVarianceGammaModel.getAssetValue(double time, int assetIndex)
RandomVariable	MonteCarloVarianceGammaModel.getAssetValue(int timeIndex, int assetIndex)
RandomVariable[]	MonteCarloMultiAssetBlackScholesModel.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	MonteCarloMultiAssetBlackScholesModel.getFactorLoading(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	MonteCarloMultiAssetBlackScholesModel.getInitialState(MonteCarloProcess process)
RandomVariable	MonteCarloAssetModel.getMonteCarloWeights(double time)
RandomVariable	MonteCarloAssetModel.getMonteCarloWeights(int timeIndex)
RandomVariable	MonteCarloBlackScholesModel.getMonteCarloWeights(double time)
RandomVariable	MonteCarloBlackScholesModel.getMonteCarloWeights(int timeIndex)
RandomVariable	MonteCarloMertonModel.getMonteCarloWeights(double time)
RandomVariable	MonteCarloMertonModel.getMonteCarloWeights(int timeIndex)
RandomVariable	MonteCarloMultiAssetBlackScholesModel.getMonteCarloWeights(double time)
RandomVariable	MonteCarloMultiAssetBlackScholesModel.getMonteCarloWeights(int timeIndex)
RandomVariable	MonteCarloVarianceGammaModel.getMonteCarloWeights(double time)
RandomVariable	MonteCarloVarianceGammaModel.getMonteCarloWeights(int timeIndex)
RandomVariable	AssetModelMonteCarloSimulationModel.getNumeraire(double time)	Returns the numeraire associated with the valuation measure used by this model.
RandomVariable	AssetModelMonteCarloSimulationModel.getNumeraire(int timeIndex)	Returns the numeraire associated with the valuation measure used by this model.
RandomVariable	MonteCarloAssetModel.getNumeraire(double time)
RandomVariable	MonteCarloAssetModel.getNumeraire(int timeIndex)
RandomVariable	MonteCarloBlackScholesModel.getNumeraire(double time)
RandomVariable	MonteCarloBlackScholesModel.getNumeraire(int timeIndex)
RandomVariable	MonteCarloMertonModel.getNumeraire(double time)
RandomVariable	MonteCarloMertonModel.getNumeraire(int timeIndex)
RandomVariable	MonteCarloMultiAssetBlackScholesModel.getNumeraire(double time)
RandomVariable	MonteCarloMultiAssetBlackScholesModel.getNumeraire(int timeIndex)
RandomVariable	MonteCarloMultiAssetBlackScholesModel.getNumeraire(MonteCarloProcess process, double time)
RandomVariable	MonteCarloVarianceGammaModel.getNumeraire(double time)
RandomVariable	MonteCarloVarianceGammaModel.getNumeraire(int timeIndex)
RandomVariable	MonteCarloAssetModel.getRandomVariableForConstant(double value)
RandomVariable	MonteCarloBlackScholesModel.getRandomVariableForConstant(double value)
RandomVariable	MonteCarloMertonModel.getRandomVariableForConstant(double value)
RandomVariable	MonteCarloMultiAssetBlackScholesModel.getRandomVariableForConstant(double value)
RandomVariable	MonteCarloVarianceGammaModel.getRandomVariableForConstant(double value)

Methods in net.finmath.montecarlo.assetderivativevaluation with parameters of type RandomVariable

Modifier and Type	Method	Description
RandomVariable	MonteCarloMultiAssetBlackScholesModel.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	MonteCarloMultiAssetBlackScholesModel.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable[]	MonteCarloMultiAssetBlackScholesModel.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	MonteCarloMultiAssetBlackScholesModel.getFactorLoading(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)

Uses of RandomVariable in net.finmath.montecarlo.assetderivativevaluation.models

Methods in net.finmath.montecarlo.assetderivativevaluation.models that return RandomVariable

Modifier and Type	Method	Description
RandomVariable	BachelierModel.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	BlackScholesModel.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	BlackScholesModelWithCurves.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	DisplacedLognomalModel.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	HestonModel.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	InhomogeneousDisplacedLognomalModel.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	InhomogenousBachelierModel.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	MertonModel.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	VarianceGammaModel.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	BachelierModel.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	BlackScholesModel.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	BlackScholesModelWithCurves.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	DisplacedLognomalModel.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	HestonModel.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	InhomogeneousDisplacedLognomalModel.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	InhomogenousBachelierModel.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	MertonModel.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	VarianceGammaModel.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	VarianceGammaModel.getDiscountRate()
RandomVariable	DisplacedLognomalModel.getDisplacement()
RandomVariable	InhomogeneousDisplacedLognomalModel.getDisplacement()
RandomVariable[]	BachelierModel.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	BlackScholesModel.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	BlackScholesModelWithCurves.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	DisplacedLognomalModel.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	HestonModel.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	InhomogeneousDisplacedLognomalModel.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	InhomogenousBachelierModel.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	MertonModel.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	VarianceGammaModel.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	BachelierModel.getFactorLoading(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	BlackScholesModel.getFactorLoading(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	BlackScholesModelWithCurves.getFactorLoading(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	DisplacedLognomalModel.getFactorLoading(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	HestonModel.getFactorLoading(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	InhomogeneousDisplacedLognomalModel.getFactorLoading(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	InhomogenousBachelierModel.getFactorLoading(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	MertonModel.getFactorLoading(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	VarianceGammaModel.getFactorLoading(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex)
RandomVariable	BachelierModel.getImpliedBachelierVolatility(double maturity)
RandomVariable	InhomogenousBachelierModel.getImpliedBachelierVolatility(double maturity)
RandomVariable[]	BachelierModel.getInitialState(MonteCarloProcess process)
RandomVariable[]	BlackScholesModel.getInitialState(MonteCarloProcess process)
RandomVariable[]	BlackScholesModelWithCurves.getInitialState(MonteCarloProcess process)
RandomVariable[]	DisplacedLognomalModel.getInitialState(MonteCarloProcess process)
RandomVariable[]	HestonModel.getInitialState(MonteCarloProcess process)
RandomVariable[]	InhomogeneousDisplacedLognomalModel.getInitialState(MonteCarloProcess process)
RandomVariable[]	InhomogenousBachelierModel.getInitialState(MonteCarloProcess process)
RandomVariable[]	MertonModel.getInitialState(MonteCarloProcess process)
RandomVariable[]	VarianceGammaModel.getInitialState(MonteCarloProcess process)
RandomVariable	BachelierModel.getInitialValue()	Returns the initial value parameter of this model.
RandomVariable[]	BlackScholesModel.getInitialValue(MonteCarloProcess process)	Return the initial value of this model.
RandomVariable[]	BlackScholesModelWithCurves.getInitialValue(MonteCarloProcess process)	Return the initial value of this model.
RandomVariable	DisplacedLognomalModel.getInitialValue()
RandomVariable	HestonModel.getInitialValue()
RandomVariable	InhomogeneousDisplacedLognomalModel.getInitialValue()
RandomVariable	InhomogenousBachelierModel.getInitialValue()	Returns the initial value parameter of this model.
RandomVariable	MertonModel.getJumpIntensity()
RandomVariable	MertonModel.getJumpSizeMean()
RandomVariable	MertonModel.getJumpSizeStdDev()
RandomVariable	HestonModel.getKappa()
RandomVariable	VarianceGammaModel.getNu()
RandomVariable	BachelierModel.getNumeraire(MonteCarloProcess process, double time)
RandomVariable	BlackScholesModel.getNumeraire(MonteCarloProcess process, double time)
RandomVariable	BlackScholesModelWithCurves.getNumeraire(MonteCarloProcess process, double time)
RandomVariable	DisplacedLognomalModel.getNumeraire(MonteCarloProcess process, double time)
RandomVariable	HestonModel.getNumeraire(MonteCarloProcess process, double time)
RandomVariable	InhomogeneousDisplacedLognomalModel.getNumeraire(MonteCarloProcess process, double time)
RandomVariable	InhomogenousBachelierModel.getNumeraire(MonteCarloProcess process, double time)
RandomVariable	MertonModel.getNumeraire(MonteCarloProcess process, double time)
RandomVariable	VarianceGammaModel.getNumeraire(MonteCarloProcess process, double time)
RandomVariable	BachelierModel.getRandomVariableForConstant(double value)
RandomVariable	BlackScholesModel.getRandomVariableForConstant(double value)
RandomVariable	BlackScholesModelWithCurves.getRandomVariableForConstant(double value)
RandomVariable	DisplacedLognomalModel.getRandomVariableForConstant(double value)
RandomVariable	HestonModel.getRandomVariableForConstant(double value)
RandomVariable	InhomogeneousDisplacedLognomalModel.getRandomVariableForConstant(double value)
RandomVariable	InhomogenousBachelierModel.getRandomVariableForConstant(double value)
RandomVariable	MertonModel.getRandomVariableForConstant(double value)
RandomVariable	VarianceGammaModel.getRandomVariableForConstant(double value)
RandomVariable	HestonModel.getRho()
RandomVariable	BachelierModel.getRiskFreeRate()	Returns the risk free rate parameter of this model.
RandomVariable	BlackScholesModel.getRiskFreeRate()	Returns the risk free rate parameter of this model.
RandomVariable	DisplacedLognomalModel.getRiskFreeRate()	Returns the risk free rate parameter of this model.
RandomVariable	HestonModel.getRiskFreeRate()	Returns the risk free rate parameter of this model.
RandomVariable	InhomogeneousDisplacedLognomalModel.getRiskFreeRate()	Returns the risk free rate parameter of this model.
RandomVariable	InhomogenousBachelierModel.getRiskFreeRate()	Returns the risk free rate parameter of this model.
RandomVariable	MertonModel.getRiskFreeRate()
RandomVariable	VarianceGammaModel.getRiskFreeRate()
RandomVariable	VarianceGammaModel.getSigma()
RandomVariable	HestonModel.getTheta()
RandomVariable	VarianceGammaModel.getTheta()
RandomVariable	BachelierModel.getVolatility()	Returns the volatility parameter of this model.
RandomVariable	BlackScholesModel.getVolatility()	Returns the volatility parameter of this model.
RandomVariable	BlackScholesModelWithCurves.getVolatility()	Returns the volatility parameter of this model.
RandomVariable	DisplacedLognomalModel.getVolatility()	Returns the volatility parameter of this model.
RandomVariable	HestonModel.getVolatility()	Returns the volatility parameter of this model.
RandomVariable	InhomogeneousDisplacedLognomalModel.getVolatility()	Returns the volatility parameter of this model.
RandomVariable	InhomogenousBachelierModel.getVolatility()	Returns the volatility parameter of this model.
RandomVariable	MertonModel.getVolatility()
RandomVariable	HestonModel.getXi()

Methods in net.finmath.montecarlo.assetderivativevaluation.models with parameters of type RandomVariable

Modifier and Type	Method	Description
RandomVariable	BachelierModel.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	BlackScholesModel.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	BlackScholesModelWithCurves.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	DisplacedLognomalModel.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	HestonModel.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	InhomogeneousDisplacedLognomalModel.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	InhomogenousBachelierModel.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	MertonModel.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	VarianceGammaModel.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	BachelierModel.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	BlackScholesModel.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	BlackScholesModelWithCurves.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	DisplacedLognomalModel.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	HestonModel.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	InhomogeneousDisplacedLognomalModel.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	InhomogenousBachelierModel.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	MertonModel.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	VarianceGammaModel.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable[]	BachelierModel.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	BlackScholesModel.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	BlackScholesModelWithCurves.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	DisplacedLognomalModel.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	HestonModel.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	InhomogeneousDisplacedLognomalModel.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	InhomogenousBachelierModel.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	MertonModel.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	VarianceGammaModel.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	BachelierModel.getFactorLoading(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	BlackScholesModel.getFactorLoading(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	BlackScholesModelWithCurves.getFactorLoading(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	DisplacedLognomalModel.getFactorLoading(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	HestonModel.getFactorLoading(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	InhomogeneousDisplacedLognomalModel.getFactorLoading(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	InhomogenousBachelierModel.getFactorLoading(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	MertonModel.getFactorLoading(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	VarianceGammaModel.getFactorLoading(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex)

Constructors in net.finmath.montecarlo.assetderivativevaluation.models with parameters of type RandomVariable

Constructor	Description
BachelierModel(RandomVariableFactory randomVariableFactory, RandomVariable initialValue, RandomVariable riskFreeRate, RandomVariable volatility)	Create a Monte-Carlo simulation using given time discretization.
BlackScholesModel(RandomVariable initialValue, RandomVariable riskFreeRate, RandomVariable volatility, RandomVariableFactory abstractRandomVariableFactory)	Create a Black-Scholes specification implementing AbstractProcessModel.
BlackScholesModelWithCurves(RandomVariable initialValue, DiscountCurve discountCurveForForwardRate, RandomVariable volatility, DiscountCurve discountCurveForDiscountRate, RandomVariableFactory abstractRandomVariableFactory)	Create a Black-Scholes specification implementing AbstractProcessModel.
DisplacedLognomalModel(RandomVariableFactory randomVariableFactory, RandomVariable initialValue, RandomVariable riskFreeRate, RandomVariable displacement, RandomVariable volatility)	Create a Monte-Carlo simulation using given time discretization.
HestonModel(RandomVariable initialValue, DiscountCurve discountCurveForForwardRate, RandomVariable volatility, DiscountCurve discountCurveForDiscountRate, RandomVariable theta, RandomVariable kappa, RandomVariable xi, RandomVariable rho, HestonModel.Scheme scheme, RandomVariableFactory randomVariableFactory)	Create a Heston model.
HestonModel(RandomVariable initialValue, RandomVariable riskFreeRate, RandomVariable volatility, RandomVariable discountRate, RandomVariable theta, RandomVariable kappa, RandomVariable xi, RandomVariable rho, HestonModel.Scheme scheme, RandomVariableFactory randomVariableFactory)	Create a Heston model.
InhomogeneousDisplacedLognomalModel(RandomVariableFactory randomVariableFactory, RandomVariable initialValue, RandomVariable riskFreeRate, RandomVariable displacement, RandomVariable volatility, boolean isUseMilsteinCorrection)	Create a blended normal/lognormal model.
InhomogenousBachelierModel(RandomVariableFactory randomVariableFactory, RandomVariable initialValue, RandomVariable riskFreeRate, RandomVariable volatility)
MertonModel(RandomVariable initialValue, DiscountCurve discountCurveForForwardRate, RandomVariable volatility, DiscountCurve discountCurveForDiscountRate, RandomVariable jumpIntensity, RandomVariable jumpSizeMean, RandomVariable jumpSizeStDev, RandomVariableFactory randomVariableFactory)	Create a Merton model.
MertonModel(RandomVariable initialValue, RandomVariable riskFreeRate, RandomVariable volatility, RandomVariable discountRate, RandomVariable jumpIntensity, RandomVariable jumpSizeMean, RandomVariable jumpSizeStDev, RandomVariableFactory randomVariableFactory)	Create a Merton model.
VarianceGammaModel(RandomVariable initialValue, DiscountCurve discountCurveForForwardRate, DiscountCurve discountCurveForDiscountRate, RandomVariable sigma, RandomVariable theta, RandomVariable nu, RandomVariableFactory randomVariableFactory)	Construct a Variance Gamma model with discount curves for the forward price (i.e. repo rate minus dividend yield) and for discounting.
VarianceGammaModel(RandomVariable initialValue, RandomVariable riskFreeRate, RandomVariable discountRate, RandomVariable sigma, RandomVariable theta, RandomVariable nu, RandomVariableFactory randomVariableFactory)	Construct a Variance Gamma model with constant rates for the forward price (i.e. repo rate minus dividend yield) and for the discount curve.

Uses of RandomVariable in net.finmath.montecarlo.assetderivativevaluation.products

Methods in net.finmath.montecarlo.assetderivativevaluation.products that return RandomVariable

Modifier and Type	Method	Description
RandomVariable	EuropeanOptionWithBoundary.getBoundaryAdjustment(double fromTime, double toTime, AssetModelMonteCarloSimulationModel model, RandomVariable continuationValues)
RandomVariable	BermudanOption.getLastValuationExerciseTime()
abstract RandomVariable	AbstractAssetMonteCarloProduct.getValue(double evaluationTime, AssetModelMonteCarloSimulationModel model)
RandomVariable	AbstractAssetMonteCarloProduct.getValue(double evaluationTime, MonteCarloSimulationModel model)
RandomVariable	AsianOption.getValue(double evaluationTime, AssetModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	AssetMonteCarloProduct.getValue(double evaluationTime, AssetModelMonteCarloSimulationModel model)
RandomVariable	BasketOption.getValue(double evaluationTime, AssetModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	BermudanDigitalOption.getValue(double evaluationTime, AssetModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	BermudanOption.getValue(double evaluationTime, AssetModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	BlackScholesDeltaHedgedPortfolio.getValue(double evaluationTime, AssetModelMonteCarloSimulationModel model)
RandomVariable	BlackScholesHedgedPortfolio.getValue(double evaluationTime, AssetModelMonteCarloSimulationModel model)
RandomVariable	DeltaHedgedPortfolioWithAAD.getValue(double evaluationTime, AssetModelMonteCarloSimulationModel model)
RandomVariable	DigitalOption.getValue(double evaluationTime, AssetModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	DigitalOptionDeltaLikelihood.getValue(double evaluationTime, AssetModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	EuropeanOption.getValue(double evaluationTime, AssetModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	EuropeanOptionDeltaLikelihood.getValue(double evaluationTime, AssetModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	EuropeanOptionDeltaPathwise.getValue(double evaluationTime, AssetModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	EuropeanOptionDeltaPathwiseForGeometricModel.getValue(double evaluationTime, AssetModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	EuropeanOptionThetaPathwise.getValue(double evaluationTime, AssetModelMonteCarloSimulationModel model)
RandomVariable	EuropeanOptionVegaPathwise.getValue(double evaluationTime, AssetModelMonteCarloSimulationModel model)
RandomVariable	EuropeanOptionWithBoundary.getValue(double evaluationTime, AssetModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	FiniteDifferenceDeltaHedgedPortfolio.getValue(double evaluationTime, AssetModelMonteCarloSimulationModel model)
RandomVariable	FiniteDifferenceHedgedPortfolio.getValue(double evaluationTime, AssetModelMonteCarloSimulationModel model)
RandomVariable	LocalRiskMinimizingHedgePortfolio.getValue(double evaluationTime, AssetModelMonteCarloSimulationModel model)

Methods in net.finmath.montecarlo.assetderivativevaluation.products with parameters of type RandomVariable

Modifier and Type	Method	Description
RandomVariableFromDoubleArray[]	EuropeanOptionWithBoundary.ConstantBarrier.getBarrierDirection(int timeIndex, RandomVariable[] realizationPredictor)
RandomVariableFromDoubleArray	EuropeanOptionWithBoundary.ConstantBarrier.getBarrierLevel(int timeIndex, RandomVariable[] realizationPredictor)
RandomVariable	EuropeanOptionWithBoundary.getBoundaryAdjustment(double fromTime, double toTime, AssetModelMonteCarloSimulationModel model, RandomVariable continuationValues)

Uses of RandomVariable in net.finmath.montecarlo.automaticdifferentiation

Subinterfaces of RandomVariable in net.finmath.montecarlo.automaticdifferentiation

Modifier and Type	Interface	Description
interface	RandomVariableDifferentiable	Interface providing additional methods for random variable implementing RandomVariable allowing automatic differentiation.

Methods in net.finmath.montecarlo.automaticdifferentiation that return RandomVariable

Modifier and Type	Method	Description
RandomVariable	AbstractRandomVariableDifferentiableFactory.createRandomVariableNonDifferentiable(double time, double value)
RandomVariable	AbstractRandomVariableDifferentiableFactory.createRandomVariableNonDifferentiable(double time, double[] values)
RandomVariable	RandomVariableDifferentiableFactory.createRandomVariableNonDifferentiable(double time, double value)	Create a (deterministic) random variable, which is not differentiable, from a constant.
RandomVariable	RandomVariableDifferentiableFactory.createRandomVariableNonDifferentiable(double time, double[] values)	Create a random variable, which is not differentiable, from an array using a specific filtration time.

Methods in net.finmath.montecarlo.automaticdifferentiation that return types with arguments of type RandomVariable

Modifier and Type	Method	Description
default Map<Long,RandomVariable>	RandomVariableDifferentiable.getGradient()	Returns the gradient of this random variable with respect to all its leaf nodes.
Map<Long,RandomVariable>	RandomVariableDifferentiable.getGradient(Set<Long> independentIDs)	Returns the gradient of this random variable with respect to the given IDs.
default Map<String,RandomVariable>	IndependentModelParameterProvider.getModelParameters()	Returns a map of independent model parameters of this model.
default Map<Long,RandomVariable>	RandomVariableDifferentiable.getTangents()	Returns the tangents of this random variable with respect to all its dependent nodes.
Map<Long,RandomVariable>	RandomVariableDifferentiable.getTangents(Set<Long> dependentIDs)	Returns the tangents of this random variable with respect to the given dependent node IDs (if dependent).

Uses of RandomVariable in net.finmath.montecarlo.automaticdifferentiation.backward

Classes in net.finmath.montecarlo.automaticdifferentiation.backward that implement RandomVariable

Modifier and Type	Class	Description
class	RandomVariableDifferentiableAAD	Implementation of RandomVariableDifferentiable using the backward algorithmic differentiation (adjoint algorithmic differentiation, AAD).

Methods in net.finmath.montecarlo.automaticdifferentiation.backward that return RandomVariable

Modifier and Type	Method	Description
RandomVariable	RandomVariableDifferentiableAAD.abs()
RandomVariable	RandomVariableDifferentiableAAD.accrue(RandomVariable rate, double periodLength)
RandomVariable	RandomVariableDifferentiableAAD.add(double value)
RandomVariable	RandomVariableDifferentiableAAD.add(RandomVariable randomVariable)
RandomVariable	RandomVariableDifferentiableAAD.addProduct(RandomVariable factor1, double factor2)
RandomVariable	RandomVariableDifferentiableAAD.addProduct(RandomVariable factor1, RandomVariable factor2)
RandomVariable	RandomVariableDifferentiableAAD.addRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	RandomVariableDifferentiableAAD.apply(DoubleBinaryOperator operator, RandomVariable argument)
RandomVariable	RandomVariableDifferentiableAAD.apply(DoubleUnaryOperator operator)
RandomVariable	RandomVariableDifferentiableAAD.apply(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2)
RandomVariable	RandomVariableDifferentiableAAD.average()
RandomVariable	RandomVariableDifferentiableAAD.bus(RandomVariable randomVariable)
RandomVariable	RandomVariableDifferentiableAAD.cache()
RandomVariable	RandomVariableDifferentiableAAD.cap(double cap)
RandomVariable	RandomVariableDifferentiableAAD.cap(RandomVariable randomVariable)
RandomVariable	RandomVariableDifferentiableAAD.choose(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative)
RandomVariable	RandomVariableDifferentiableAAD.cos()
RandomVariable	RandomVariableDifferentiableAAD.discount(RandomVariable rate, double periodLength)
RandomVariable	RandomVariableDifferentiableAAD.div(double value)
RandomVariable	RandomVariableDifferentiableAAD.div(RandomVariable randomVariable)
RandomVariable	RandomVariableDifferentiableAAD.exp()
RandomVariable	RandomVariableDifferentiableAAD.floor(double floor)
RandomVariable	RandomVariableDifferentiableAAD.floor(RandomVariable floor)
RandomVariable	RandomVariableDifferentiableAAD.getConditionalExpectation(ConditionalExpectationEstimator estimator)
RandomVariable	RandomVariableDifferentiableAAD.getMaxAsRandomVariableAAD()
RandomVariable	RandomVariableDifferentiableAAD.getMinAsRandomVariableAAD()
RandomVariable	RandomVariableDifferentiableAAD.getSampleVarianceAsRandomVariableAAD()
RandomVariable	RandomVariableDifferentiableAAD.getStandardDeviationAsRandomVariableAAD()
RandomVariable	RandomVariableDifferentiableAAD.getStandardErrorAsRandomVariableAAD()
RandomVariable	RandomVariableDifferentiableAAD.getValues()	Returns the underlying values.
RandomVariable	RandomVariableDifferentiableAAD.getVarianceAsRandomVariableAAD()
RandomVariable	RandomVariableDifferentiableAAD.invert()
RandomVariable	RandomVariableDifferentiableAAD.isNaN()
RandomVariable	RandomVariableDifferentiableAAD.log()
RandomVariable	RandomVariableDifferentiableAAD.mult(double value)
RandomVariable	RandomVariableDifferentiableAAD.mult(RandomVariable randomVariable)
RandomVariable	RandomVariableDifferentiableAAD.pow(double exponent)
RandomVariable	RandomVariableDifferentiableAAD.sin()
RandomVariable	RandomVariableDifferentiableAAD.sqrt()
RandomVariable	RandomVariableDifferentiableAAD.squared()
RandomVariable	RandomVariableDifferentiableAAD.sub(double value)
RandomVariable	RandomVariableDifferentiableAAD.sub(RandomVariable randomVariable)
RandomVariable	RandomVariableDifferentiableAAD.subRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	RandomVariableDifferentiableAAD.vid(RandomVariable randomVariable)

Methods in net.finmath.montecarlo.automaticdifferentiation.backward that return types with arguments of type RandomVariable

Modifier and Type	Method	Description
Map<Long,RandomVariable>	RandomVariableDifferentiableAAD.getGradient(Set<Long> independentIDs)	Returns the gradient of this random variable with respect to all its leaf nodes.
Map<Long,RandomVariable>	RandomVariableDifferentiableAAD.getTangents(Set<Long> dependentIDs)

Methods in net.finmath.montecarlo.automaticdifferentiation.backward with parameters of type RandomVariable

Modifier and Type	Method	Description
RandomVariable	RandomVariableDifferentiableAAD.accrue(RandomVariable rate, double periodLength)
RandomVariable	RandomVariableDifferentiableAAD.add(RandomVariable randomVariable)
RandomVariable	RandomVariableDifferentiableAAD.addProduct(RandomVariable factor1, double factor2)
RandomVariable	RandomVariableDifferentiableAAD.addProduct(RandomVariable factor1, RandomVariable factor2)
RandomVariable	RandomVariableDifferentiableAAD.addRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	RandomVariableDifferentiableAAD.apply(DoubleBinaryOperator operator, RandomVariable argument)
RandomVariable	RandomVariableDifferentiableAAD.apply(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2)
RandomVariable	RandomVariableDifferentiableAAD.bus(RandomVariable randomVariable)
RandomVariable	RandomVariableDifferentiableAAD.cap(RandomVariable randomVariable)
RandomVariable	RandomVariableDifferentiableAAD.choose(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative)
RandomVariable	RandomVariableDifferentiableAAD.discount(RandomVariable rate, double periodLength)
RandomVariable	RandomVariableDifferentiableAAD.div(RandomVariable randomVariable)
boolean	RandomVariableDifferentiableAAD.equals(RandomVariable randomVariable)
RandomVariable	RandomVariableDifferentiableAAD.floor(RandomVariable floor)
double	RandomVariableDifferentiableAAD.getAverage(RandomVariable probabilities)
double	RandomVariableDifferentiableAAD.getQuantile(double quantile, RandomVariable probabilities)
double	RandomVariableDifferentiableAAD.getStandardDeviation(RandomVariable probabilities)
double	RandomVariableDifferentiableAAD.getStandardError(RandomVariable probabilities)
double	RandomVariableDifferentiableAAD.getVariance(RandomVariable probabilities)
RandomVariable	RandomVariableDifferentiableAAD.mult(RandomVariable randomVariable)
static RandomVariableDifferentiableAAD	RandomVariableDifferentiableAAD.of(RandomVariable randomVariable)
RandomVariable	RandomVariableDifferentiableAAD.sub(RandomVariable randomVariable)
RandomVariable	RandomVariableDifferentiableAAD.subRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	RandomVariableDifferentiableAAD.vid(RandomVariable randomVariable)

Constructors in net.finmath.montecarlo.automaticdifferentiation.backward with parameters of type RandomVariable

Constructor	Description
RandomVariableDifferentiableAAD(RandomVariable randomVariable)
RandomVariableDifferentiableAAD(RandomVariable values, List<net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD.OperatorTreeNode> argumentOperatorTreeNodes, List<RandomVariable> argumentValues, ConditionalExpectationEstimator estimator, net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD.OperatorType operator, RandomVariableDifferentiableAADFactory factory, int methodArgumentTypePriority)
RandomVariableDifferentiableAAD(RandomVariable values, List<RandomVariable> arguments, ConditionalExpectationEstimator estimator, net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD.OperatorType operator, RandomVariableDifferentiableAADFactory factory)
RandomVariableDifferentiableAAD(RandomVariable values, List<RandomVariable> arguments, ConditionalExpectationEstimator estimator, net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD.OperatorType operator, RandomVariableDifferentiableAADFactory factory, int methodArgumentTypePriority)
RandomVariableDifferentiableAAD(RandomVariable values, RandomVariableDifferentiableAADFactory factory)

Constructor parameters in net.finmath.montecarlo.automaticdifferentiation.backward with type arguments of type RandomVariable

Constructor	Description
RandomVariableDifferentiableAAD(RandomVariable values, List<RandomVariable> arguments, ConditionalExpectationEstimator estimator, net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD.OperatorType operator, RandomVariableDifferentiableAADFactory factory)
RandomVariableDifferentiableAAD(RandomVariable values, List<RandomVariable> arguments, ConditionalExpectationEstimator estimator, net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD.OperatorType operator, RandomVariableDifferentiableAADFactory factory, int methodArgumentTypePriority)

Uses of RandomVariable in net.finmath.montecarlo.automaticdifferentiation.forward

Classes in net.finmath.montecarlo.automaticdifferentiation.forward that implement RandomVariable

Modifier and Type	Class	Description
class	RandomVariableDifferentiableAD	Implementation of RandomVariableDifferentiable using the forward algorithmic differentiation (AD).

Methods in net.finmath.montecarlo.automaticdifferentiation.forward that return RandomVariable

Modifier and Type	Method	Description
RandomVariable	RandomVariableDifferentiableAD.abs()
RandomVariable	RandomVariableDifferentiableAD.accrue(RandomVariable rate, double periodLength)
RandomVariable	RandomVariableDifferentiableAD.add(double value)
RandomVariable	RandomVariableDifferentiableAD.add(RandomVariable randomVariable)
RandomVariable	RandomVariableDifferentiableAD.addProduct(RandomVariable factor1, double factor2)
RandomVariable	RandomVariableDifferentiableAD.addProduct(RandomVariable factor1, RandomVariable factor2)
RandomVariable	RandomVariableDifferentiableAD.addRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	RandomVariableDifferentiableAD.apply(DoubleBinaryOperator operator, RandomVariable argument)
RandomVariable	RandomVariableDifferentiableAD.apply(DoubleUnaryOperator operator)
RandomVariable	RandomVariableDifferentiableAD.apply(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2)
RandomVariable	RandomVariableDifferentiableAD.average()
RandomVariable	RandomVariableDifferentiableAD.bus(RandomVariable randomVariable)
RandomVariable	RandomVariableDifferentiableAD.cache()
RandomVariable	RandomVariableDifferentiableAD.cap(double cap)
RandomVariable	RandomVariableDifferentiableAD.cap(RandomVariable randomVariable)
RandomVariable	RandomVariableDifferentiableAD.choose(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative)
RandomVariable	RandomVariableDifferentiableAD.cos()
RandomVariable	RandomVariableDifferentiableAD.discount(RandomVariable rate, double periodLength)
RandomVariable	RandomVariableDifferentiableAD.div(double value)
RandomVariable	RandomVariableDifferentiableAD.div(RandomVariable randomVariable)
RandomVariable	RandomVariableDifferentiableAD.exp()
RandomVariable	RandomVariableDifferentiableAD.floor(double floor)
RandomVariable	RandomVariableDifferentiableAD.floor(RandomVariable floor)
RandomVariable	RandomVariableDifferentiableAD.getConditionalExpectation(ConditionalExpectationEstimator estimator)
RandomVariable	RandomVariableDifferentiableAD.getMaxAsRandomVariableAAD()
RandomVariable	RandomVariableDifferentiableAD.getMinAsRandomVariableAAD()
RandomVariable	RandomVariableDifferentiableAD.getSampleVarianceAsRandomVariableAAD()
RandomVariable	RandomVariableDifferentiableAD.getStandardDeviationAsRandomVariableAAD()
RandomVariable	RandomVariableDifferentiableAD.getStandardErrorAsRandomVariableAAD()
RandomVariable	RandomVariableDifferentiableAD.getValues()	Returns the underlying values.
RandomVariable	RandomVariableDifferentiableAD.getVarianceAsRandomVariableAAD()
RandomVariable	RandomVariableDifferentiableAD.invert()
RandomVariable	RandomVariableDifferentiableAD.isNaN()
RandomVariable	RandomVariableDifferentiableAD.log()
RandomVariable	RandomVariableDifferentiableAD.mult(double value)
RandomVariable	RandomVariableDifferentiableAD.mult(RandomVariable randomVariable)
RandomVariable	RandomVariableDifferentiableAD.pow(double exponent)
RandomVariable	RandomVariableDifferentiableAD.sin()
RandomVariable	RandomVariableDifferentiableAD.sqrt()
RandomVariable	RandomVariableDifferentiableAD.squared()
RandomVariable	RandomVariableDifferentiableAD.sub(double value)
RandomVariable	RandomVariableDifferentiableAD.sub(RandomVariable randomVariable)
RandomVariable	RandomVariableDifferentiableAD.subRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	RandomVariableDifferentiableAD.vid(RandomVariable randomVariable)

Methods in net.finmath.montecarlo.automaticdifferentiation.forward that return types with arguments of type RandomVariable

Modifier and Type	Method	Description
Map<Long,RandomVariable>	RandomVariableDifferentiableAD.getGradient(Set<Long> independentIDs)	Returns the gradient of this random variable with respect to all its leaf nodes.
Map<Long,RandomVariable>	RandomVariableDifferentiableAD.getTangents()
Map<Long,RandomVariable>	RandomVariableDifferentiableAD.getTangents(Set<Long> dependentIDs)

Methods in net.finmath.montecarlo.automaticdifferentiation.forward with parameters of type RandomVariable

Modifier and Type	Method	Description
RandomVariable	RandomVariableDifferentiableAD.accrue(RandomVariable rate, double periodLength)
RandomVariable	RandomVariableDifferentiableAD.add(RandomVariable randomVariable)
RandomVariable	RandomVariableDifferentiableAD.addProduct(RandomVariable factor1, double factor2)
RandomVariable	RandomVariableDifferentiableAD.addProduct(RandomVariable factor1, RandomVariable factor2)
RandomVariable	RandomVariableDifferentiableAD.addRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	RandomVariableDifferentiableAD.apply(DoubleBinaryOperator operator, RandomVariable argument)
RandomVariable	RandomVariableDifferentiableAD.apply(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2)
RandomVariable	RandomVariableDifferentiableAD.bus(RandomVariable randomVariable)
RandomVariable	RandomVariableDifferentiableAD.cap(RandomVariable randomVariable)
RandomVariable	RandomVariableDifferentiableAD.choose(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative)
RandomVariable	RandomVariableDifferentiableAD.discount(RandomVariable rate, double periodLength)
RandomVariable	RandomVariableDifferentiableAD.div(RandomVariable randomVariable)
boolean	RandomVariableDifferentiableAD.equals(RandomVariable randomVariable)
RandomVariable	RandomVariableDifferentiableAD.floor(RandomVariable floor)
double	RandomVariableDifferentiableAD.getAverage(RandomVariable probabilities)
double	RandomVariableDifferentiableAD.getQuantile(double quantile, RandomVariable probabilities)
double	RandomVariableDifferentiableAD.getStandardDeviation(RandomVariable probabilities)
double	RandomVariableDifferentiableAD.getStandardError(RandomVariable probabilities)
double	RandomVariableDifferentiableAD.getVariance(RandomVariable probabilities)
RandomVariable	RandomVariableDifferentiableAD.mult(RandomVariable randomVariable)
static RandomVariableDifferentiableAD	RandomVariableDifferentiableAD.of(RandomVariable randomVariable)
RandomVariable	RandomVariableDifferentiableAD.sub(RandomVariable randomVariable)
RandomVariable	RandomVariableDifferentiableAD.subRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	RandomVariableDifferentiableAD.vid(RandomVariable randomVariable)

Constructors in net.finmath.montecarlo.automaticdifferentiation.forward with parameters of type RandomVariable

Constructor	Description
RandomVariableDifferentiableAD(RandomVariable randomVariable)
RandomVariableDifferentiableAD(RandomVariable values, List<RandomVariable> arguments, ConditionalExpectationEstimator estimator, net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD.OperatorType operator)
RandomVariableDifferentiableAD(RandomVariable values, List<RandomVariable> arguments, ConditionalExpectationEstimator estimator, net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD.OperatorType operator, int methodArgumentTypePriority)

Constructor parameters in net.finmath.montecarlo.automaticdifferentiation.forward with type arguments of type RandomVariable

Constructor	Description
RandomVariableDifferentiableAD(RandomVariable values, List<RandomVariable> arguments, ConditionalExpectationEstimator estimator, net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD.OperatorType operator)
RandomVariableDifferentiableAD(RandomVariable values, List<RandomVariable> arguments, ConditionalExpectationEstimator estimator, net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD.OperatorType operator, int methodArgumentTypePriority)

Uses of RandomVariable in net.finmath.montecarlo.conditionalexpectation

Methods in net.finmath.montecarlo.conditionalexpectation that return RandomVariable

Modifier and Type	Method	Description
RandomVariable[]	MonteCarloConditionalExpectationRegression.RegressionBasisFunctions.getBasisFunctions()
RandomVariable[]	MonteCarloConditionalExpectationRegression.RegressionBasisFunctionsGiven.getBasisFunctions()
RandomVariable[]	RegressionBasisFunctionsFromProducts.getBasisFunctions(double evaluationTime, MonteCarloSimulationModel model)
RandomVariable[]	RegressionBasisFunctionsProvider.getBasisFunctions(double evaluationTime, MonteCarloSimulationModel model)	Provides a set of \( \mathcal{F}_{t} \)-measurable random variables which can serve as regression basis functions.
RandomVariable	MonteCarloConditionalExpectationRegression.getConditionalExpectation(RandomVariable randomVariable)

Methods in net.finmath.montecarlo.conditionalexpectation with parameters of type RandomVariable

Modifier and Type	Method	Description
RandomVariable	MonteCarloConditionalExpectationRegression.getConditionalExpectation(RandomVariable randomVariable)
ConditionalExpectationEstimator	MonteCarloConditionalExpectationLinearRegressionFactory.getConditionalExpectationEstimator(RandomVariable[] basisFunctionsEstimator, RandomVariable[] basisFunctionsPredictor)
ConditionalExpectationEstimator	MonteCarloConditionalExpectationLocalizedOnDependentRegressionFactory.getConditionalExpectationEstimator(RandomVariable[] basisFunctionsEstimator, RandomVariable[] basisFunctionsPredictor)
ConditionalExpectationEstimator	MonteCarloConditionalExpectationRegressionFactory.getConditionalExpectationEstimator(RandomVariable[] basisFunctionsEstimator, RandomVariable[] basisFunctionsPredictor)	Creates an object implementing a ConditionalExpectationEstimator for conditional expectation estimation.
double[]	MonteCarloConditionalExpectationRegression.getLinearRegressionParameters(RandomVariable dependents)	Return the solution x of XTX x = XT y for a given y.
double[]	MonteCarloConditionalExpectationRegressionLocalizedOnDependents.getLinearRegressionParameters(RandomVariable dependents)	Return the solution x of XTX x = XT y for a given y.
double[]	LinearRegression.getRegressionCoefficients(RandomVariable value)	Get the vector of regression coefficients.

Constructors in net.finmath.montecarlo.conditionalexpectation with parameters of type RandomVariable

Constructor	Description
LinearRegression(RandomVariable[] basisFunctions)	Create the linear regression with a set of basis functions.
MonteCarloConditionalExpectationRegression(RandomVariable[] basisFunctions)	Creates a class for conditional expectation estimation.
MonteCarloConditionalExpectationRegression(RandomVariable[] basisFunctionsEstimator, RandomVariable[] basisFunctionsPredictor)	Creates a class for conditional expectation estimation.
MonteCarloConditionalExpectationRegressionLocalizedOnDependents(RandomVariable[] basisFunctions)	Creates a class for conditional expectation estimation.
MonteCarloConditionalExpectationRegressionLocalizedOnDependents(RandomVariable[] basisFunctionsEstimator, double standardDeviations)	Creates a class for conditional expectation estimation.
MonteCarloConditionalExpectationRegressionLocalizedOnDependents(RandomVariable[] basisFunctionsEstimator, RandomVariable[] basisFunctionsPredictor)	Creates a class for conditional expectation estimation.
MonteCarloConditionalExpectationRegressionLocalizedOnDependents(RandomVariable[] basisFunctionsEstimator, RandomVariable[] basisFunctionsPredictor, double standardDeviations)	Creates a class for conditional expectation estimation.
RegressionBasisFunctionsGiven(RandomVariable[] basisFunctions)

Uses of RandomVariable in net.finmath.montecarlo.crosscurrency

Methods in net.finmath.montecarlo.crosscurrency that return RandomVariable

Modifier and Type	Method	Description
RandomVariable	CrossCurrencyTermStructureMonteCarloSimulationModel.getExchangeRate(String fromCurve, String toCurve, double time)	Return the (cross curve or currency) exchange rate for a given simulation time.
RandomVariable	CrossCurrencyTermStructureMonteCarloSimulationModel.getForwardRate(String curve, double time, double periodStart, double periodEnd)	Return the forward rate for a given simulation time and a given period start and period end.
RandomVariable	CrossCurrencyTermStructureMonteCarloSimulationModel.getNumeraire(double time)	Return the numeraire at a given time.

Uses of RandomVariable in net.finmath.montecarlo.hybridassetinterestrate

Methods in net.finmath.montecarlo.hybridassetinterestrate that return RandomVariable

Modifier and Type	Method	Description
RandomVariable	HybridAssetLIBORModelMonteCarloSimulationFromModels.getAssetValue(double time, int assetIndex)
RandomVariable	HybridAssetLIBORModelMonteCarloSimulationFromModels.getAssetValue(int timeIndex, int assetIndex)
RandomVariable[]	ConvexityAdjustedModel.getDrift(RandomVariable[] driftUnadjusted, MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable	HybridAssetLIBORModelMonteCarloSimulationFromModels.getLIBOR(double time, double periodStart, double periodEnd)
RandomVariable	HybridAssetLIBORModelMonteCarloSimulationFromModels.getLIBOR(int timeIndex, int liborIndex)
RandomVariable[]	HybridAssetLIBORModelMonteCarloSimulationFromModels.getLIBORs(int timeIndex)
RandomVariable	CrossCurrencyLIBORMarketModelFromModels.getMonteCarloWeights(double time)
RandomVariable	CrossCurrencyLIBORMarketModelFromModels.getMonteCarloWeights(int timeIndex)
RandomVariable	HybridAssetLIBORModelMonteCarloSimulationFromModels.getMonteCarloWeights(double time)
RandomVariable	HybridAssetLIBORModelMonteCarloSimulationFromModels.getMonteCarloWeights(int timeIndex)
RandomVariable	CrossCurrencyLIBORMarketModelFromModels.getNumeraire(double time)
RandomVariable	CrossCurrencyLIBORMarketModelFromModels.getNumeraire(String account, double time)
RandomVariable	HybridAssetLIBORModelMonteCarloSimulationFromModels.getNumeraire(double time)
RandomVariable	HybridAssetLIBORModelMonteCarloSimulationFromModels.getNumeraire(int timeIndex)
RandomVariable	HybridAssetMonteCarloSimulation.getNumeraire(double time)	Return the (default) numeraire at a given time.
RandomVariable	HybridAssetMonteCarloSimulation.getNumeraire(String account, double time)	Return the numeraire associated with a given (collateral or funding) account at a given time.
RandomVariable	CrossCurrencyLIBORMarketModelFromModels.getRandomVariableForConstant(double value)
RandomVariable	HybridAssetLIBORModelMonteCarloSimulationFromModels.getRandomVariableForConstant(double value)
RandomVariable	CrossCurrencyLIBORMarketModelFromModels.getValue(RiskFactorID riskFactorIdentifyer, double time)
RandomVariable	HybridAssetMonteCarloSimulation.getValue(RiskFactorID riskFactorIdentifyer, double time)	Return the random variable of a risk factor with a given name at a given observation time index.

Methods in net.finmath.montecarlo.hybridassetinterestrate that return types with arguments of type RandomVariable

Modifier and Type	Method	Description
Map<String,RandomVariable>	HybridAssetLIBORModelMonteCarloSimulationFromModels.getModelParameters()

Methods in net.finmath.montecarlo.hybridassetinterestrate with parameters of type RandomVariable

Modifier and Type	Method	Description
RandomVariable[]	ConvexityAdjustedModel.getDrift(RandomVariable[] driftUnadjusted, MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)

Uses of RandomVariable in net.finmath.montecarlo.hybridassetinterestrate.products

Methods in net.finmath.montecarlo.hybridassetinterestrate.products that return RandomVariable

Modifier and Type	Method	Description
RandomVariable	Bond.getValue(double evaluationTime, HybridAssetMonteCarloSimulation model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	BondWithForeignNumeraire.getValue(double evaluationTime, HybridAssetMonteCarloSimulation model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	ForwardRateAgreementGeneralized.getValue(double evaluationTime, HybridAssetMonteCarloSimulation model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
abstract RandomVariable	HybridAssetMonteCarloProduct.getValue(double evaluationTime, HybridAssetMonteCarloSimulation model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	HybridAssetMonteCarloProduct.getValue(double evaluationTime, MonteCarloSimulationModel model)
RandomVariable	HybridAssetMonteCarloProduct.getValueForModifiedData(double evaluationTime, MonteCarloSimulationModel monteCarloSimulationInterface, Map<String,Object> dataModified)

Constructors in net.finmath.montecarlo.hybridassetinterestrate.products with parameters of type RandomVariable

Constructor	Description
ForwardRateAgreementGeneralized(LocalDateTime referenceDate, String currency, double fixing, double periodStart, double periodEnd, RandomVariable spread, RandomVariable cap, RandomVariable floor)

Uses of RandomVariable in net.finmath.montecarlo.interestrate

Methods in net.finmath.montecarlo.interestrate that return RandomVariable

Modifier and Type	Method	Description
default RandomVariable	TermStructureModel.getForwardDiscountBond(MonteCarloProcess process, double time, double maturity)	Returns the time \( t \) forward bond derived from the numeraire, i.e., \( P(T;t) = E( \frac{N(t)}{N(T)} \vert \mathcal{F}_{t} ) \).
RandomVariable	LIBORModel.getLIBOR(MonteCarloProcess process, int timeIndex, int liborIndex)	Return the forward rate at a given timeIndex and for a given liborIndex.
RandomVariable	LIBORModelMonteCarloSimulationModel.getLIBOR(int timeIndex, int liborIndex)	Return the forward rate for a given simulation time index and a given forward rate index.
RandomVariable	LIBORMonteCarloSimulationFromLIBORModel.getLIBOR(double time, double periodStart, double periodEnd)
RandomVariable	LIBORMonteCarloSimulationFromLIBORModel.getLIBOR(int timeIndex, int liborIndex)
RandomVariable	LIBORMonteCarloSimulationFromTermStructureModel.getLIBOR(double time, double periodStart, double periodEnd)
RandomVariable	LIBORMonteCarloSimulationFromTermStructureModel.getLIBOR(int timeIndex, int liborIndex)
RandomVariable	TermStructureModel.getLIBOR(MonteCarloProcess process, double time, double periodStart, double periodEnd)	Returns the time \( t \) forward rate on the models forward curve.
RandomVariable	TermStructureMonteCarloSimulationModel.getLIBOR(double time, double periodStart, double periodEnd)	Return the forward rate for a given simulation time and a given period start and period end.
default RandomVariable	TermStructureMonteCarloSimulationModel.getLIBOR(LocalDateTime date, LocalDateTime periodStartDate, LocalDateTime periodEndDate)	Return the forward rate for a given simulation time and a given period start and period end.
RandomVariable[]	LIBORModelMonteCarloSimulationModel.getLIBORs(int timeIndex)	Return the forward rate curve for a given simulation time index.
RandomVariable[]	LIBORMonteCarloSimulationFromLIBORModel.getLIBORs(int timeIndex)
RandomVariable[]	LIBORMonteCarloSimulationFromTermStructureModel.getLIBORs(int timeIndex)
RandomVariable	LIBORMonteCarloSimulationFromLIBORModel.getMonteCarloWeights(double time)
RandomVariable	LIBORMonteCarloSimulationFromLIBORModel.getMonteCarloWeights(int timeIndex)
RandomVariable	LIBORMonteCarloSimulationFromTermStructureModel.getMonteCarloWeights(double time)
RandomVariable	LIBORMonteCarloSimulationFromTermStructureModel.getMonteCarloWeights(int timeIndex)
RandomVariable	LIBORMonteCarloSimulationFromLIBORModel.getNumeraire(double time)
RandomVariable	LIBORMonteCarloSimulationFromTermStructureModel.getNumeraire(double time)
RandomVariable	TermStructureMonteCarloSimulationModel.getNumeraire(double time)	Return the numeraire at a given time.
default RandomVariable	TermStructureMonteCarloSimulationModel.getNumeraire(LocalDateTime date)	Return the numeraire at a given time.
RandomVariable	LIBORMonteCarloSimulationFromLIBORModel.getRandomVariableForConstant(double value)
RandomVariable	LIBORMonteCarloSimulationFromTermStructureModel.getRandomVariableForConstant(double value)
RandomVariable	CalibrationProduct.getTargetValue()

Methods in net.finmath.montecarlo.interestrate that return types with arguments of type RandomVariable

Modifier and Type	Method	Description
Map<String,RandomVariable>	LIBORMonteCarloSimulationFromLIBORModel.getModelParameters()
Map<String,RandomVariable>	LIBORMonteCarloSimulationFromTermStructureModel.getModelParameters()

Constructors in net.finmath.montecarlo.interestrate with parameters of type RandomVariable

Constructor	Description
CalibrationProduct(String name, AbstractLIBORMonteCarloProduct product, RandomVariable targetValue, double weight)
CalibrationProduct(String name, AbstractLIBORMonteCarloProduct product, RandomVariable targetValue, double weight, int priority)	Construct a calibration product.
CalibrationProduct(AbstractLIBORMonteCarloProduct product, RandomVariable targetValue, double weight)

Uses of RandomVariable in net.finmath.montecarlo.interestrate.models

Methods in net.finmath.montecarlo.interestrate.models that return RandomVariable

Modifier and Type	Method	Description
RandomVariable	HullWhiteModel.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	HullWhiteModelWithConstantCoeff.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	HullWhiteModelWithDirectSimulation.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	HullWhiteModelWithShiftExtension.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	LIBORMarketModelFromCovarianceModel.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	LIBORMarketModelStandard.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	LIBORMarketModelWithTenorRefinement.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	HullWhiteModel.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	HullWhiteModelWithConstantCoeff.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	HullWhiteModelWithDirectSimulation.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	HullWhiteModelWithShiftExtension.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	LIBORMarketModelFromCovarianceModel.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	LIBORMarketModelStandard.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	LIBORMarketModelWithTenorRefinement.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable[]	HullWhiteModel.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	HullWhiteModelWithConstantCoeff.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	HullWhiteModelWithDirectSimulation.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	HullWhiteModelWithShiftExtension.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	LIBORMarketModelFromCovarianceModel.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)	Return the complete vector of the drift for the time index timeIndex, given that current state is realizationAtTimeIndex.
RandomVariable[]	LIBORMarketModelStandard.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)	Return the complete vector of the drift for the time index timeIndex, given that current state is realizationAtTimeIndex.
RandomVariable[]	LIBORMarketModelWithTenorRefinement.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)	Return the complete vector of the drift for the time index timeIndex, given that current state is realizationAtTimeIndex.
protected RandomVariable	LIBORMarketModelStandard.getDriftEuler(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] liborVectorStart)
RandomVariable[]	HullWhiteModel.getFactorLoading(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	HullWhiteModelWithConstantCoeff.getFactorLoading(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	HullWhiteModelWithDirectSimulation.getFactorLoading(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	HullWhiteModelWithShiftExtension.getFactorLoading(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	LIBORMarketModelFromCovarianceModel.getFactorLoading(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	LIBORMarketModelStandard.getFactorLoading(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	LIBORMarketModelWithTenorRefinement.getFactorLoading(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex)
RandomVariable	HullWhiteModel.getForwardDiscountBond(MonteCarloProcess process, double time, double maturity)
RandomVariable	LIBORMarketModelFromCovarianceModel.getForwardDiscountBond(MonteCarloProcess process, double time, double maturity)
RandomVariable[]	HullWhiteModel.getInitialState(MonteCarloProcess process)
RandomVariable[]	HullWhiteModelWithConstantCoeff.getInitialState(MonteCarloProcess process)
RandomVariable[]	HullWhiteModelWithDirectSimulation.getInitialState(MonteCarloProcess process)
RandomVariable[]	HullWhiteModelWithShiftExtension.getInitialState(MonteCarloProcess process)
RandomVariable[]	LIBORMarketModelFromCovarianceModel.getInitialState(MonteCarloProcess process)
RandomVariable[]	LIBORMarketModelStandard.getInitialState(MonteCarloProcess process)
RandomVariable[]	LIBORMarketModelWithTenorRefinement.getInitialState(MonteCarloProcess process)
RandomVariable	HullWhiteModel.getIntegratedBondSquaredVolatility(double time, double maturity)
RandomVariable	HullWhiteModel.getLIBOR(MonteCarloProcess process, double time, double periodStart, double periodEnd)
RandomVariable	HullWhiteModel.getLIBOR(MonteCarloProcess process, int timeIndex, int liborIndex)
RandomVariable	HullWhiteModelWithConstantCoeff.getLIBOR(MonteCarloProcess process, double time, double periodStart, double periodEnd)
RandomVariable	HullWhiteModelWithConstantCoeff.getLIBOR(MonteCarloProcess process, int timeIndex, int liborIndex)
RandomVariable	HullWhiteModelWithDirectSimulation.getLIBOR(MonteCarloProcess process, double time, double periodStart, double periodEnd)
RandomVariable	HullWhiteModelWithDirectSimulation.getLIBOR(MonteCarloProcess process, int timeIndex, int liborIndex)
RandomVariable	HullWhiteModelWithShiftExtension.getLIBOR(MonteCarloProcess process, double time, double periodStart, double periodEnd)
RandomVariable	HullWhiteModelWithShiftExtension.getLIBOR(MonteCarloProcess process, int timeIndex, int liborIndex)
RandomVariable	LIBORMarketModelFromCovarianceModel.getLIBOR(MonteCarloProcess process, double time, double periodStart, double periodEnd)
RandomVariable	LIBORMarketModelFromCovarianceModel.getLIBOR(MonteCarloProcess process, int timeIndex, int liborIndex)
RandomVariable	LIBORMarketModelStandard.getLIBOR(MonteCarloProcess process, double time, double periodStart, double periodEnd)
RandomVariable	LIBORMarketModelStandard.getLIBOR(MonteCarloProcess process, int timeIndex, int liborIndex)
RandomVariable	LIBORMarketModelWithTenorRefinement.getLIBOR(MonteCarloProcess process, double time, double periodStart, double periodEnd)
RandomVariable	LIBORMarketModelWithTenorRefinement.getLIBOR(MonteCarloProcess process, int timeIndex, double periodStart, double periodEnd)
RandomVariable	LIBORMarketModelWithTenorRefinement.getLIBORForStateVariable(TimeDiscretization liborPeriodDiscretization, RandomVariable[] stateVariables, double periodStart, double periodEnd)
RandomVariable	HullWhiteModel.getNumeraire(MonteCarloProcess process, double time)
RandomVariable	HullWhiteModelWithConstantCoeff.getNumeraire(MonteCarloProcess process, double time)
RandomVariable	HullWhiteModelWithDirectSimulation.getNumeraire(MonteCarloProcess process, double time)
RandomVariable	HullWhiteModelWithShiftExtension.getNumeraire(MonteCarloProcess process, double time)
RandomVariable	LIBORMarketModelFromCovarianceModel.getNumeraire(MonteCarloProcess process, double time)	Return the numeraire at a given time.
RandomVariable	LIBORMarketModelStandard.getNumeraire(MonteCarloProcess process, double time)	Return the numeraire at a given time.
RandomVariable	LIBORMarketModelWithTenorRefinement.getNumeraire(MonteCarloProcess process, double time)	Return the numeraire at a given time.
protected RandomVariable	LIBORMarketModelFromCovarianceModel.getNumerairetUnAdjusted(MonteCarloProcess process, double time)
protected RandomVariable	LIBORMarketModelFromCovarianceModel.getNumerairetUnAdjustedAtLIBORIndex(MonteCarloProcess process, int liborTimeIndex)
RandomVariable	HullWhiteModel.getRandomVariableForConstant(double value)
RandomVariable	HullWhiteModelWithConstantCoeff.getRandomVariableForConstant(double value)
RandomVariable	HullWhiteModelWithDirectSimulation.getRandomVariableForConstant(double value)
RandomVariable	HullWhiteModelWithShiftExtension.getRandomVariableForConstant(double value)
RandomVariable	LIBORMarketModelFromCovarianceModel.getRandomVariableForConstant(double value)
RandomVariable	LIBORMarketModelStandard.getRandomVariableForConstant(double value)
RandomVariable	LIBORMarketModelWithTenorRefinement.getRandomVariableForConstant(double value)
RandomVariable	HullWhiteModel.getShortRateConditionalVariance(double time, double maturity)	Calculates the variance \( \mathop{Var}(r(t) \vert r(s) ) \), that is \( \int_{s}^{t} \sigma^{2}(\tau) \exp(-2 \cdot \int_{\tau}^{t} a(u) \mathrm{d}u ) \ \mathrm{d}\tau \) where \( a \) is the meanReversion and \( \sigma \) is the short rate instantaneous volatility.
RandomVariable	LIBORMarketModelWithTenorRefinement.getStateVariable(MonteCarloProcess process, int timeIndex, double periodStart, double periodEnd)
RandomVariable	LIBORMarketModelWithTenorRefinement.getStateVariableForPeriod(TimeDiscretization liborPeriodDiscretization, RandomVariable[] stateVariables, double periodStart, double periodEnd)

Methods in net.finmath.montecarlo.interestrate.models that return types with arguments of type RandomVariable

Modifier and Type	Method	Description
Map<String,RandomVariable>	HullWhiteModel.getModelParameters()
Map<String,RandomVariable>	HullWhiteModelWithConstantCoeff.getModelParameters()
Map<String,RandomVariable>	HullWhiteModelWithDirectSimulation.getModelParameters()
Map<String,RandomVariable>	HullWhiteModelWithShiftExtension.getModelParameters()
Map<String,RandomVariable>	LIBORMarketModelFromCovarianceModel.getModelParameters()
Map<String,RandomVariable>	LIBORMarketModelStandard.getModelParameters()
Map<Double,RandomVariable>	LIBORMarketModelFromCovarianceModel.getNumeraireAdjustments()

Methods in net.finmath.montecarlo.interestrate.models with parameters of type RandomVariable

Modifier and Type	Method	Description
RandomVariable	HullWhiteModel.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	HullWhiteModelWithConstantCoeff.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	HullWhiteModelWithDirectSimulation.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	HullWhiteModelWithShiftExtension.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	LIBORMarketModelFromCovarianceModel.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	LIBORMarketModelStandard.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	LIBORMarketModelWithTenorRefinement.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	HullWhiteModel.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	HullWhiteModelWithConstantCoeff.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	HullWhiteModelWithDirectSimulation.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	HullWhiteModelWithShiftExtension.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	LIBORMarketModelFromCovarianceModel.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	LIBORMarketModelStandard.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	LIBORMarketModelWithTenorRefinement.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable[]	HullWhiteModel.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	HullWhiteModelWithConstantCoeff.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	HullWhiteModelWithDirectSimulation.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	HullWhiteModelWithShiftExtension.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	LIBORMarketModelFromCovarianceModel.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)	Return the complete vector of the drift for the time index timeIndex, given that current state is realizationAtTimeIndex.
RandomVariable[]	LIBORMarketModelStandard.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)	Return the complete vector of the drift for the time index timeIndex, given that current state is realizationAtTimeIndex.
RandomVariable[]	LIBORMarketModelWithTenorRefinement.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)	Return the complete vector of the drift for the time index timeIndex, given that current state is realizationAtTimeIndex.
protected RandomVariable	LIBORMarketModelStandard.getDriftEuler(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] liborVectorStart)
RandomVariable[]	HullWhiteModel.getFactorLoading(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	HullWhiteModelWithConstantCoeff.getFactorLoading(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	HullWhiteModelWithDirectSimulation.getFactorLoading(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	HullWhiteModelWithShiftExtension.getFactorLoading(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	LIBORMarketModelFromCovarianceModel.getFactorLoading(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	LIBORMarketModelStandard.getFactorLoading(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	LIBORMarketModelWithTenorRefinement.getFactorLoading(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex)
RandomVariable	LIBORMarketModelWithTenorRefinement.getLIBORForStateVariable(TimeDiscretization liborPeriodDiscretization, RandomVariable[] stateVariables, double periodStart, double periodEnd)
RandomVariable	LIBORMarketModelWithTenorRefinement.getStateVariableForPeriod(TimeDiscretization liborPeriodDiscretization, RandomVariable[] stateVariables, double periodStart, double periodEnd)

Uses of RandomVariable in net.finmath.montecarlo.interestrate.models.covariance

Methods in net.finmath.montecarlo.interestrate.models.covariance that return RandomVariable

Modifier and Type	Method	Description
RandomVariable	AbstractLIBORCovarianceModel.getCovariance(double time, int component1, int component2, RandomVariable[] realizationAtTimeIndex)
RandomVariable	AbstractLIBORCovarianceModel.getCovariance(int timeIndex, int component1, int component2, RandomVariable[] realizationAtTimeIndex)
RandomVariable	LIBORCovarianceModel.getCovariance(double time, int component1, int component2, RandomVariable[] realizationAtTimeIndex)	Returns the instantaneous covariance calculated from factor loadings.
RandomVariable	LIBORCovarianceModel.getCovariance(int timeIndex, int component1, int component2, RandomVariable[] realizationAtTimeIndex)	Returns the instantaneous covariance calculated from factor loadings.
RandomVariable	LIBORCovarianceModelFromVolatilityAndCorrelation.getCovariance(int timeIndex, int component1, int component2, RandomVariable[] realizationAtTimeIndex)
RandomVariable	DisplacedLocalVolatilityModel.getDisplacement()
RandomVariable	ExponentialDecayLocalVolatilityModel.getDisplacement()
RandomVariable[]	AbstractLIBORCovarianceModel.getFactorLoading(double time, double component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	AbstractLIBORCovarianceModel.getFactorLoading(double time, int component, RandomVariable[] realizationAtTimeIndex)
abstract RandomVariable[]	AbstractLIBORCovarianceModel.getFactorLoading(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	BlendedLocalVolatilityModel.getFactorLoading(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	DisplacedLocalVolatilityModel.getFactorLoading(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	ExponentialDecayLocalVolatilityModel.getFactorLoading(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	HullWhiteLocalVolatilityModel.getFactorLoading(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	LIBORCovarianceModel.getFactorLoading(double time, double component, RandomVariable[] realizationAtTimeIndex)	Return the factor loading for a given time and a given component.
RandomVariable[]	LIBORCovarianceModel.getFactorLoading(double time, int component, RandomVariable[] realizationAtTimeIndex)	Return the factor loading for a given time and component index.
RandomVariable[]	LIBORCovarianceModel.getFactorLoading(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)	Return the factor loading for a given time index and component index.
RandomVariable[]	LIBORCovarianceModelBH.getFactorLoading(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	LIBORCovarianceModelExponentialForm5Param.getFactorLoading(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	LIBORCovarianceModelExponentialForm7Param.getFactorLoading(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	LIBORCovarianceModelFromVolatilityAndCorrelation.getFactorLoading(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	LIBORCovarianceModelStochasticHestonVolatility.getFactorLoading(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	LIBORCovarianceModelStochasticVolatility.getFactorLoading(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	TermStructCovarianceModelFromLIBORCovarianceModel.getFactorLoading(double time, double periodStart, double periodEnd, TimeDiscretization periodDiscretization, RandomVariable[] realizationAtTimeIndex, TermStructureModel model)
RandomVariable[]	TermStructCovarianceModelFromLIBORCovarianceModelParametric.getFactorLoading(double time, double periodStart, double periodEnd, TimeDiscretization periodDiscretization, RandomVariable[] realizationAtTimeIndex, TermStructureModel model)
RandomVariable[]	TermStructureFactorLoadingsModelInterface.getFactorLoading(double time, double periodStart, double periodEnd, TimeDiscretization periodDiscretization, RandomVariable[] realizationAtTimeIndex, TermStructureModel model)	Return the factor loading for a given time and a term structure period.
abstract RandomVariable	AbstractLIBORCovarianceModel.getFactorLoadingPseudoInverse(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex)
RandomVariable	BlendedLocalVolatilityModel.getFactorLoadingPseudoInverse(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex)
RandomVariable	DisplacedLocalVolatilityModel.getFactorLoadingPseudoInverse(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex)
RandomVariable	ExponentialDecayLocalVolatilityModel.getFactorLoadingPseudoInverse(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex)
RandomVariable	HullWhiteLocalVolatilityModel.getFactorLoadingPseudoInverse(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex)
RandomVariable	LIBORCovarianceModel.getFactorLoadingPseudoInverse(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex)	Returns the pseudo inverse of the factor matrix.
RandomVariable	LIBORCovarianceModelFromVolatilityAndCorrelation.getFactorLoadingPseudoInverse(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex)
RandomVariable	LIBORCovarianceModelStochasticHestonVolatility.getFactorLoadingPseudoInverse(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex)
RandomVariable	LIBORCovarianceModelStochasticVolatility.getFactorLoadingPseudoInverse(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex)
RandomVariable	ShortRateVolatilityModel.getMeanReversion(int timeIndex)	Returns the value of \( a(t) \) for \( t_{i} \leq t < t_{i+1} \).
RandomVariable	ShortRateVolatilityModelAsGiven.getMeanReversion(int timeIndex)
RandomVariable	ShortRateVolatilityModelHoLee.getMeanReversion(int timeIndex)
RandomVariable	ShortRateVolatilityModelPiecewiseConstant.getMeanReversion(int timeIndex)
RandomVariable[]	AbstractLIBORCovarianceModelParametric.getParameter()	Get the parameters of determining this parametric covariance model.
abstract RandomVariable[]	AbstractShortRateVolatilityModelParametric.getParameter()	Get the parameters of determining this parametric volatility model.
RandomVariable[]	BlendedLocalVolatilityModel.getParameter()
RandomVariable[]	DisplacedLocalVolatilityModel.getParameter()
RandomVariable[]	ExponentialDecayLocalVolatilityModel.getParameter()
abstract RandomVariable[]	LIBORCorrelationModel.getParameter()
RandomVariable[]	LIBORCorrelationModelExponentialDecay.getParameter()
RandomVariable[]	LIBORCorrelationModelThreeParameterExponentialDecay.getParameter()
RandomVariable[]	LIBORCovarianceModelExponentialForm5Param.getParameter()
RandomVariable[]	LIBORCovarianceModelFromVolatilityAndCorrelation.getParameter()
RandomVariable[]	LIBORCovarianceModelStochasticHestonVolatility.getParameter()
RandomVariable[]	LIBORCovarianceModelStochasticVolatility.getParameter()
abstract RandomVariable[]	LIBORVolatilityModel.getParameter()
RandomVariable[]	LIBORVolatilityModelFourParameterExponentialForm.getParameter()
RandomVariable[]	LIBORVolatilityModelFourParameterExponentialFormIntegrated.getParameter()
RandomVariable[]	LIBORVolatilityModelFromGivenMatrix.getParameter()
RandomVariable[]	LIBORVolatilityModelMaturityDependentFourParameterExponentialForm.getParameter()
RandomVariable[]	LIBORVolatilityModelPiecewiseConstant.getParameter()
RandomVariable[]	LIBORVolatilityModelTimeHomogenousPiecewiseConstant.getParameter()
RandomVariable[]	LIBORVolatilityModelTwoParameterExponentialForm.getParameter()
RandomVariable[]	ShortRateVolatilityModelParametric.getParameter()	Get the parameters of determining this parametric volatility model.
RandomVariable[]	ShortRateVolatilityModelPiecewiseConstant.getParameter()
abstract RandomVariable	LIBORVolatilityModel.getVolatility(int timeIndex, int component)	Implement this method to complete the implementation.
RandomVariable	LIBORVolatilityModelFourParameterExponentialForm.getVolatility(int timeIndex, int liborIndex)
RandomVariable	LIBORVolatilityModelFourParameterExponentialFormIntegrated.getVolatility(int timeIndex, int liborIndex)
RandomVariable	LIBORVolatilityModelFromGivenMatrix.getVolatility(int timeIndex, int component)
RandomVariable	LIBORVolatilityModelMaturityDependentFourParameterExponentialForm.getVolatility(int timeIndex, int liborIndex)
RandomVariable	LIBORVolatilityModelPiecewiseConstant.getVolatility(int timeIndex, int liborIndex)
RandomVariable	LIBORVolatilityModelTimeHomogenousPiecewiseConstant.getVolatility(int timeIndex, int liborIndex)
RandomVariable	LIBORVolatilityModelTwoParameterExponentialForm.getVolatility(int timeIndex, int liborIndex)
RandomVariable	ShortRateVolatilityModel.getVolatility(int timeIndex)	Returns the value of \( \sigma(t) \) for \( t_{i} \leq t < t_{i+1} \).
RandomVariable	ShortRateVolatilityModelAsGiven.getVolatility(int timeIndex)
RandomVariable	ShortRateVolatilityModelHoLee.getVolatility(int timeIndex)
RandomVariable	ShortRateVolatilityModelPiecewiseConstant.getVolatility(double time)
RandomVariable	ShortRateVolatilityModelPiecewiseConstant.getVolatility(int timeIndex)

Methods in net.finmath.montecarlo.interestrate.models.covariance with parameters of type RandomVariable

Modifier and Type	Method	Description
abstract LIBORCorrelationModel	LIBORCorrelationModel.getCloneWithModifiedParameter(RandomVariable[] parameter)
LIBORCorrelationModelExponentialDecay	LIBORCorrelationModelExponentialDecay.getCloneWithModifiedParameter(RandomVariable[] parameter)
LIBORCorrelationModelThreeParameterExponentialDecay	LIBORCorrelationModelThreeParameterExponentialDecay.getCloneWithModifiedParameter(RandomVariable[] parameter)
abstract LIBORVolatilityModel	LIBORVolatilityModel.getCloneWithModifiedParameter(RandomVariable[] parameter)
LIBORVolatilityModelFourParameterExponentialForm	LIBORVolatilityModelFourParameterExponentialForm.getCloneWithModifiedParameter(RandomVariable[] parameter)
LIBORVolatilityModelFourParameterExponentialFormIntegrated	LIBORVolatilityModelFourParameterExponentialFormIntegrated.getCloneWithModifiedParameter(RandomVariable[] parameter)
LIBORVolatilityModelFromGivenMatrix	LIBORVolatilityModelFromGivenMatrix.getCloneWithModifiedParameter(RandomVariable[] parameter)
LIBORVolatilityModelMaturityDependentFourParameterExponentialForm	LIBORVolatilityModelMaturityDependentFourParameterExponentialForm.getCloneWithModifiedParameter(RandomVariable[] parameter)
LIBORVolatilityModel	LIBORVolatilityModelPiecewiseConstant.getCloneWithModifiedParameter(RandomVariable[] parameter)
LIBORVolatilityModelTimeHomogenousPiecewiseConstant	LIBORVolatilityModelTimeHomogenousPiecewiseConstant.getCloneWithModifiedParameter(RandomVariable[] parameter)
LIBORVolatilityModelTwoParameterExponentialForm	LIBORVolatilityModelTwoParameterExponentialForm.getCloneWithModifiedParameter(RandomVariable[] parameter)
AbstractLIBORCovarianceModelParametric	AbstractLIBORCovarianceModelParametric.getCloneWithModifiedParameters(RandomVariable[] parameters)	Return an instance of this model using a new set of parameters.
abstract AbstractShortRateVolatilityModelParametric	AbstractShortRateVolatilityModelParametric.getCloneWithModifiedParameters(RandomVariable[] parameters)	Return an instance of this model using a new set of parameters.
AbstractLIBORCovarianceModelParametric	BlendedLocalVolatilityModel.getCloneWithModifiedParameters(RandomVariable[] parameters)
AbstractLIBORCovarianceModelParametric	DisplacedLocalVolatilityModel.getCloneWithModifiedParameters(RandomVariable[] parameters)
AbstractLIBORCovarianceModelParametric	ExponentialDecayLocalVolatilityModel.getCloneWithModifiedParameters(RandomVariable[] parameters)
AbstractLIBORCovarianceModelParametric	LIBORCovarianceModelExponentialForm5Param.getCloneWithModifiedParameters(RandomVariable[] parameters)
AbstractLIBORCovarianceModelParametric	LIBORCovarianceModelFromVolatilityAndCorrelation.getCloneWithModifiedParameters(RandomVariable[] parameters)
AbstractLIBORCovarianceModelParametric	LIBORCovarianceModelStochasticHestonVolatility.getCloneWithModifiedParameters(RandomVariable[] parameters)
AbstractLIBORCovarianceModelParametric	LIBORCovarianceModelStochasticVolatility.getCloneWithModifiedParameters(RandomVariable[] parameters)
ShortRateVolatilityModelParametric	ShortRateVolatilityModelParametric.getCloneWithModifiedParameters(RandomVariable[] parameters)	Return an instance of this model using a new set of parameters.
AbstractShortRateVolatilityModelParametric	ShortRateVolatilityModelPiecewiseConstant.getCloneWithModifiedParameters(RandomVariable[] parameters)
RandomVariable	AbstractLIBORCovarianceModel.getCovariance(double time, int component1, int component2, RandomVariable[] realizationAtTimeIndex)
RandomVariable	AbstractLIBORCovarianceModel.getCovariance(int timeIndex, int component1, int component2, RandomVariable[] realizationAtTimeIndex)
RandomVariable	LIBORCovarianceModel.getCovariance(double time, int component1, int component2, RandomVariable[] realizationAtTimeIndex)	Returns the instantaneous covariance calculated from factor loadings.
RandomVariable	LIBORCovarianceModel.getCovariance(int timeIndex, int component1, int component2, RandomVariable[] realizationAtTimeIndex)	Returns the instantaneous covariance calculated from factor loadings.
RandomVariable	LIBORCovarianceModelFromVolatilityAndCorrelation.getCovariance(int timeIndex, int component1, int component2, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	AbstractLIBORCovarianceModel.getFactorLoading(double time, double component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	AbstractLIBORCovarianceModel.getFactorLoading(double time, int component, RandomVariable[] realizationAtTimeIndex)
abstract RandomVariable[]	AbstractLIBORCovarianceModel.getFactorLoading(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	BlendedLocalVolatilityModel.getFactorLoading(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	DisplacedLocalVolatilityModel.getFactorLoading(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	ExponentialDecayLocalVolatilityModel.getFactorLoading(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	HullWhiteLocalVolatilityModel.getFactorLoading(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	LIBORCovarianceModel.getFactorLoading(double time, double component, RandomVariable[] realizationAtTimeIndex)	Return the factor loading for a given time and a given component.
RandomVariable[]	LIBORCovarianceModel.getFactorLoading(double time, int component, RandomVariable[] realizationAtTimeIndex)	Return the factor loading for a given time and component index.
RandomVariable[]	LIBORCovarianceModel.getFactorLoading(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)	Return the factor loading for a given time index and component index.
RandomVariable[]	LIBORCovarianceModelBH.getFactorLoading(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	LIBORCovarianceModelExponentialForm5Param.getFactorLoading(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	LIBORCovarianceModelExponentialForm7Param.getFactorLoading(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	LIBORCovarianceModelFromVolatilityAndCorrelation.getFactorLoading(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	LIBORCovarianceModelStochasticHestonVolatility.getFactorLoading(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	LIBORCovarianceModelStochasticVolatility.getFactorLoading(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	TermStructCovarianceModelFromLIBORCovarianceModel.getFactorLoading(double time, double periodStart, double periodEnd, TimeDiscretization periodDiscretization, RandomVariable[] realizationAtTimeIndex, TermStructureModel model)
RandomVariable[]	TermStructCovarianceModelFromLIBORCovarianceModelParametric.getFactorLoading(double time, double periodStart, double periodEnd, TimeDiscretization periodDiscretization, RandomVariable[] realizationAtTimeIndex, TermStructureModel model)
RandomVariable[]	TermStructureFactorLoadingsModelInterface.getFactorLoading(double time, double periodStart, double periodEnd, TimeDiscretization periodDiscretization, RandomVariable[] realizationAtTimeIndex, TermStructureModel model)	Return the factor loading for a given time and a term structure period.
abstract RandomVariable	AbstractLIBORCovarianceModel.getFactorLoadingPseudoInverse(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex)
RandomVariable	BlendedLocalVolatilityModel.getFactorLoadingPseudoInverse(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex)
RandomVariable	DisplacedLocalVolatilityModel.getFactorLoadingPseudoInverse(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex)
RandomVariable	ExponentialDecayLocalVolatilityModel.getFactorLoadingPseudoInverse(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex)
RandomVariable	HullWhiteLocalVolatilityModel.getFactorLoadingPseudoInverse(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex)
RandomVariable	LIBORCovarianceModel.getFactorLoadingPseudoInverse(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex)	Returns the pseudo inverse of the factor matrix.
RandomVariableFromDoubleArray	LIBORCovarianceModelBH.getFactorLoadingPseudoInverse(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex)
RandomVariableFromDoubleArray	LIBORCovarianceModelExponentialForm5Param.getFactorLoadingPseudoInverse(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex)
RandomVariableFromDoubleArray	LIBORCovarianceModelExponentialForm7Param.getFactorLoadingPseudoInverse(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex)
RandomVariable	LIBORCovarianceModelFromVolatilityAndCorrelation.getFactorLoadingPseudoInverse(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex)
RandomVariable	LIBORCovarianceModelStochasticHestonVolatility.getFactorLoadingPseudoInverse(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex)
RandomVariable	LIBORCovarianceModelStochasticVolatility.getFactorLoadingPseudoInverse(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex)

Constructors in net.finmath.montecarlo.interestrate.models.covariance with parameters of type RandomVariable

Constructor	Description
BlendedLocalVolatilityModel(AbstractLIBORCovarianceModelParametric covarianceModel, ForwardCurve forwardCurve, RandomVariable displacement, boolean isCalibrateable)	Displaced diffusion model build on top of a standard covariance model.
DisplacedLocalVolatilityModel(AbstractLIBORCovarianceModelParametric covarianceModel, RandomVariable displacement, boolean isCalibrateable)	Displaced model build on top of a standard covariance model.
ExponentialDecayLocalVolatilityModel(RandomVariableFactory abstractRandomVariableFactory, AbstractLIBORCovarianceModelParametric covarianceModel, RandomVariable decay, boolean isCalibrateable)	Exponential decay model build on top of a standard covariance model.
LIBORCovarianceModelExponentialForm5Param(TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, int numberOfFactors, RandomVariable[] parameters)
LIBORCovarianceModelStochasticHestonVolatility(AbstractLIBORCovarianceModelParametric covarianceModel, BrownianMotion brownianMotion, RandomVariable kappa, RandomVariable theta, RandomVariable xi, boolean isCalibrateable)	Create a modification of a given AbstractLIBORCovarianceModelParametric with a stochastic volatility scaling.
LIBORCovarianceModelStochasticVolatility(AbstractLIBORCovarianceModelParametric covarianceModel, BrownianMotion brownianMotion, RandomVariable nu, RandomVariable rho, boolean isCalibrateable)	Create a modification of a given AbstractLIBORCovarianceModelParametric with a stochastic volatility scaling.
LIBORVolatilityModelFourParameterExponentialForm(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, RandomVariable a, RandomVariable b, RandomVariable c, RandomVariable d, boolean isCalibrateable)	Creates the volatility model σi(tj) = ( a + b * (Ti-tj) ) * exp(-c (Ti-tj)) + d
LIBORVolatilityModelFourParameterExponentialForm(TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, RandomVariable a, RandomVariable b, RandomVariable c, RandomVariable d, boolean isCalibrateable)	Creates the volatility model σi(tj) = ( a + b * (Ti-tj) ) * exp(-c (Ti-tj)) + d
LIBORVolatilityModelFourParameterExponentialFormIntegrated(TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, RandomVariable a, RandomVariable b, RandomVariable c, RandomVariable d, boolean isCalibrateable)	Creates the volatility model \[ \sigma_{i}(t_{j}) = \sqrt{ \frac{1}{t_{j+1}-t_{j}} \int_{t_{j}}^{t_{j+1}} \left( ( a + b (T_{i}-t) ) \exp(-c (T_{i}-t)) + d \right)^{2} \ \mathrm{d}t } \text{
LIBORVolatilityModelFromGivenMatrix(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, RandomVariable[][] volatility, boolean isCalibrateable)	Creates a simple volatility model using given piece-wise constant values on a given discretization grid.
LIBORVolatilityModelFromGivenMatrix(TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, RandomVariable[][] volatility)	Creates a simple volatility model using given piece-wise constant values on a given discretization grid.
LIBORVolatilityModelFromGivenMatrix(TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, RandomVariable[][] volatility, boolean isCalibrateable)	Creates a simple volatility model using given piece-wise constant values on a given discretization grid.
LIBORVolatilityModelMaturityDependentFourParameterExponentialForm(TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, RandomVariable[] parameterA, RandomVariable[] parameterB, RandomVariable[] parameterC, RandomVariable[] parameterD)
LIBORVolatilityModelPiecewiseConstant(TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, TimeDiscretization simulationTimeDiscretization, TimeDiscretization timeToMaturityDiscretization, RandomVariable[] volatility, boolean isCalibrateable)
LIBORVolatilityModelTimeHomogenousPiecewiseConstant(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, TimeDiscretization timeToMaturityDiscretization, RandomVariable[] volatility)	Create a piecewise constant volatility model, where \( \sigma(t,T) = sigma_{i} \) where \( i = \max \{ j : \tau_{j} \leq T-t \} \) and \( \tau_{0}, \tau_{1}, \ldots, \tau_{n-1} \) is a given time discretization.
LIBORVolatilityModelTimeHomogenousPiecewiseConstant(TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, TimeDiscretization timeToMaturityDiscretization, RandomVariable[] volatility)	Create a piecewise constant volatility model, where \( \sigma(t,T) = sigma_{i} \) where \( i = \max \{ j : \tau_{j} \leq T-t \} \) and \( \tau_{0}, \tau_{1}, \ldots, \tau_{n-1} \) is a given time discretization.
LIBORVolatilityModelTwoParameterExponentialForm(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, RandomVariable a, RandomVariable b, boolean isCalibrateable)	Creates the volatility model σi(tj) = a * exp(-b (Ti-tj))
ShortRateVolatilityModelPiecewiseConstant(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization volatilityTimeDiscretization, RandomVariable[] volatility, RandomVariable[] meanReversion, boolean isVolatilityCalibrateable)
ShortRateVolatilityModelPiecewiseConstant(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization volatilityTimeDiscretization, RandomVariable[] volatility, RandomVariable[] meanReversion, boolean isVolatilityCalibrateable, boolean isMeanReversionCalibrateable)

Uses of RandomVariable in net.finmath.montecarlo.interestrate.products

Methods in net.finmath.montecarlo.interestrate.products that return RandomVariable

Modifier and Type	Method	Description
RandomVariable[]	BermudanSwaption.getBasisFunctions(double fixingDate, LIBORModelMonteCarloSimulationModel model)	Return the basis functions for the regression suitable for this product.
RandomVariable[]	BermudanSwaption.getBasisFunctions(double fixingDate, MonteCarloSimulationModel model)	Return the basis functions for the regression suitable for this product.
RandomVariable[]	BermudanSwaptionFromSwapSchedules.getBasisFunctions(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	Provides a set of \( \mathcal{F}_{t} \)-measurable random variables which can serve as regression basis functions.
RandomVariable[]	BermudanSwaptionFromSwapSchedules.getBasisFunctions(double evaluationTime, MonteCarloSimulationModel model)
RandomVariable	Swaption.getExerciseIndicator(LIBORModelMonteCarloSimulationModel model)	Deprecated.
RandomVariable	SwaptionATM.getImpliedBachelierATMOptionVolatility(RandomVariable optionValue, double optionMaturity, double swapAnnuity)	Calculates ATM Bachelier implied volatilities.
abstract RandomVariable	AbstractLIBORMonteCarloProduct.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	AbstractLIBORMonteCarloProduct.getValue(double evaluationTime, MonteCarloSimulationModel model)
RandomVariable	BermudanSwaption.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	BermudanSwaptionFromSwapSchedules.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	Bond.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	CancelableSwap.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	Caplet.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	CMSOption.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	DigitalCaplet.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	DigitalFloorlet.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	FlexiCap.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	ForwardRateVolatilitySurfaceCurvature.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	LIBORBond.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	MoneyMarketAccount.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	Portfolio.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	SimpleCappedFlooredFloatingRateBond.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	SimpleSwap.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	SimpleZeroSwap.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	Swap.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	SwapLeg.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	SwaprateCovarianceAnalyticApproximation.getValue(double evaluationTime, MonteCarloSimulationModel model)
RandomVariable	Swaption.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	SwaptionAnalyticApproximation.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	SwaptionAnalyticApproximationRebonato.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	SwaptionATM.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	SwaptionFromSwapSchedules.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	SwaptionGeneralizedAnalyticApproximation.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	SwaptionSimple.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	SwaptionSingleCurve.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	SwaptionSingleCurveAnalyticApproximation.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	SwaptionWithComponents.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	SwapWithComponents.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	TermStructureMonteCarloProduct.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	AbstractLIBORMonteCarloProduct.getValueForModifiedData(double evaluationTime, MonteCarloSimulationModel monteCarloSimulationModel, Map<String,Object> dataModified)
static RandomVariable	SwaptionFromSwapSchedules.getValueOfLegAnalytic(double evaluationTime, LIBORModelMonteCarloSimulationModel model, Schedule schedule, boolean paysFloatingRate, double fixRate, double notional)	Determines the time \( t \)-measurable value of a swap leg (can handle fix or float).
RandomVariable	ForwardRateVolatilitySurfaceCurvature.getValues(double evaluationTime, LIBORMarketModel model)	Calculates the squared curvature of the LIBOR instantaneous variance.
RandomVariable	SwaprateCovarianceAnalyticApproximation.getValues(double evaluationTime, TimeDiscretization timeDiscretization, LIBORMarketModel model)	Calculates the approximated integrated instantaneous covariance of two swap rates, using the approximation d log(S(t))/d log(L(t)) = d log(S(0))/d log(L(0)).
RandomVariable	SwaptionAnalyticApproximation.getValues(double evaluationTime, TimeDiscretization timeDiscretization, LIBORMarketModel model)	Calculates the approximated integrated instantaneous variance of the swap rate, using the approximation d log(S(t))/d log(L(t)) = d log(S(0))/d log(L(0)).
RandomVariable	SwaptionAnalyticApproximationRebonato.getValues(double evaluationTime, TimeDiscretization timeDiscretization, LIBORMarketModel model)	Calculates the approximated integrated instantaneous variance of the swap rate, using the approximation d log(S(t))/d log(L(t)) = d log(S(0))/d log(L(0)).
RandomVariable	SwaptionGeneralizedAnalyticApproximation.getValues(double evaluationTime, TimeDiscretization timeDiscretization, LIBORMarketModel model)	Calculates the approximated integrated instantaneous variance of the swap rate, using the approximation d S/d L (t) = d S/d L (0).
RandomVariable	SwaptionSingleCurveAnalyticApproximation.getValues(double evaluationTime, TimeDiscretization timeDiscretization, LIBORMarketModel model)	Calculates the approximated integrated instantaneous variance of the swap rate, using the approximation d log(S(t))/d log(L(t)) = d log(S(0))/d log(L(0)).

Methods in net.finmath.montecarlo.interestrate.products with parameters of type RandomVariable

Modifier and Type	Method	Description
double[]	BermudanSwaptionFromSwapSchedules.getExerciseProbabilitiesFromTimes(LocalDateTime localDateTime, RandomVariable exerciseTimes)	Determines the vector of exercise probabilities for a given RandomVariable of exerciseTimes.
RandomVariable	SwaptionATM.getImpliedBachelierATMOptionVolatility(RandomVariable optionValue, double optionMaturity, double swapAnnuity)	Calculates ATM Bachelier implied volatilities.

Uses of RandomVariable in net.finmath.montecarlo.interestrate.products.components

Methods in net.finmath.montecarlo.interestrate.products.components that return RandomVariable

Modifier and Type	Method	Description
RandomVariable[]	Option.getBasisFunctions(double exerciseDate, LIBORModelMonteCarloSimulationModel model)	Return the regression basis functions.
RandomVariable[]	Option.getBasisFunctions(double evaluationTime, MonteCarloSimulationModel model)
abstract RandomVariable	AbstractPeriod.getCoupon(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	Period.getCoupon(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	AccruingNotional.getNotionalAtPeriodEnd(AbstractPeriod period, LIBORModelMonteCarloSimulationModel model)
RandomVariable	Notional.getNotionalAtPeriodEnd(AbstractPeriod period, LIBORModelMonteCarloSimulationModel model)	Calculates the notional at the end of a period, given a period.
RandomVariable	NotionalFromComponent.getNotionalAtPeriodEnd(AbstractPeriod period, LIBORModelMonteCarloSimulationModel model)
RandomVariable	NotionalFromConstant.getNotionalAtPeriodEnd(AbstractPeriod period, LIBORModelMonteCarloSimulationModel model)
RandomVariable	AccruingNotional.getNotionalAtPeriodStart(AbstractPeriod period, LIBORModelMonteCarloSimulationModel model)
RandomVariable	Notional.getNotionalAtPeriodStart(AbstractPeriod period, LIBORModelMonteCarloSimulationModel model)	Calculates the notional at the start of a period, given a period.
RandomVariable	NotionalFromComponent.getNotionalAtPeriodStart(AbstractPeriod period, LIBORModelMonteCarloSimulationModel model)
RandomVariable	NotionalFromConstant.getNotionalAtPeriodStart(AbstractPeriod period, LIBORModelMonteCarloSimulationModel model)
abstract RandomVariable	AbstractPeriod.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	AccrualAccount.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	Cashflow.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	Choice.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	ExpectedTailLoss.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	ExposureEstimator.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	IndexedValue.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	Numeraire.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	Option.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	Period.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	ProductCollection.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.
RandomVariable	Selector.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)	This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.

Uses of RandomVariable in net.finmath.montecarlo.interestrate.products.indices

Methods in net.finmath.montecarlo.interestrate.products.indices that return RandomVariable

Modifier and Type	Method	Description
RandomVariable	FixedCoupon.getCoupon()	Returns the coupon.
abstract RandomVariable	AbstractIndex.getValue(double fixingTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	AccruedInterest.getValue(double fixingTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	AnalyticModelForwardCurveIndex.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	AnalyticModelIndex.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	CappedFlooredIndex.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	ConstantMaturitySwaprate.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	DateIndex.getValue(double fixingTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	FixedCoupon.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	ForwardCurveIndex.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	LaggedIndex.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	LIBORIndex.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	LinearCombinationIndex.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	MaxIndex.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	MinIndex.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	NumerairePerformanceIndex.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	NumerairePerformanceOnScheduleIndex.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	PerformanceIndex.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	PowIndex.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	ProductIndex.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	TimeDiscreteEndOfMonthIndex.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	TriggerIndex.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)
RandomVariable	UnsupportedIndex.getValue(double evaluationTime, LIBORModelMonteCarloSimulationModel model)

Uses of RandomVariable in net.finmath.montecarlo.model

Methods in net.finmath.montecarlo.model that return RandomVariable

Modifier and Type	Method	Description
RandomVariable	ProcessModel.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)	Applies the state space transform fi to the given state random variable such that Yi → fi(Yi) =: Xi.
default RandomVariable	ProcessModel.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)	Applies the inverse state space transform f-1i to the given random variable such that Xi → f-1i(Xi) =: Yi.
RandomVariable[]	ProcessModel.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)	This method has to be implemented to return the drift, i.e.
RandomVariable[]	ProcessModel.getFactorLoading(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex)	This method has to be implemented to return the factor loadings, i.e.
RandomVariable[]	ProcessModel.getInitialState(MonteCarloProcess process)	Returns the initial value of the state variable of the process Y, not to be confused with the initial value of the model X (which is the state space transform applied to this state value.
RandomVariable[]	AbstractProcessModel.getInitialValue(MonteCarloProcess process)	Returns the initial value of the model.
RandomVariable	ProcessModel.getNumeraire(MonteCarloProcess process, double time)	Return the numeraire at a given time index.
RandomVariable	ProcessModel.getRandomVariableForConstant(double value)	Return a random variable initialized with a constant using the models random variable factory.

Methods in net.finmath.montecarlo.model with parameters of type RandomVariable

Modifier and Type	Method	Description
RandomVariable	ProcessModel.applyStateSpaceTransform(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)	Applies the state space transform fi to the given state random variable such that Yi → fi(Yi) =: Xi.
default RandomVariable	ProcessModel.applyStateSpaceTransformInverse(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable)	Applies the inverse state space transform f-1i to the given random variable such that Xi → f-1i(Xi) =: Yi.
RandomVariable[]	ProcessModel.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)	This method has to be implemented to return the drift, i.e.
RandomVariable[]	ProcessModel.getFactorLoading(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex)	This method has to be implemented to return the factor loadings, i.e.

Uses of RandomVariable in net.finmath.montecarlo.process

Methods in net.finmath.montecarlo.process that return RandomVariable

Modifier and Type	Method	Description
RandomVariable	MonteCarloProcessFromProcessModel.applyStateSpaceTransform(int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	MonteCarloProcessFromProcessModel.applyStateSpaceTransformInverse(int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable[]	MonteCarloProcessFromProcessModel.getDrift(int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	MonteCarloProcessFromProcessModel.getFactorLoading(int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	MonteCarloProcessFromProcessModel.getInitialState()
RandomVariable	EulerSchemeFromProcessModel.getMonteCarloWeights(int timeIndex)	This method returns the weights of a weighted Monte Carlo method (the probability density).
RandomVariable	LinearInterpolatedTimeDiscreteProcess.getMonteCarloWeights(int timeIndex)
RandomVariable	Process.getMonteCarloWeights(int timeIndex)	This method returns the weights of a weighted Monte Carlo method (the probability density).
RandomVariable	EulerSchemeFromProcessModel.getProcessValue(int timeIndex, int componentIndex)	This method returns the realization of the process at a certain time index.
RandomVariable	LinearInterpolatedTimeDiscreteProcess.getProcessValue(double time, int component)	Returns the (possibly interpolated) value of this stochastic process at a given time \( t \).
RandomVariable	LinearInterpolatedTimeDiscreteProcess.getProcessValue(int timeIndex, int component)
default RandomVariable[]	Process.getProcessValue(int timeIndex)	This method returns the realization of the process for a given time index.
RandomVariable	Process.getProcessValue(int timeIndex, int componentIndex)	This method returns the realization of a component of the process for a given time index.

Methods in net.finmath.montecarlo.process with parameters of type RandomVariable

Modifier and Type	Method	Description
RandomVariable	MonteCarloProcessFromProcessModel.applyStateSpaceTransform(int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable	MonteCarloProcessFromProcessModel.applyStateSpaceTransformInverse(int timeIndex, int componentIndex, RandomVariable randomVariable)
RandomVariable[]	MonteCarloProcessFromProcessModel.getDrift(int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	MonteCarloProcessFromProcessModel.getFactorLoading(int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex)

Constructor parameters in net.finmath.montecarlo.process with type arguments of type RandomVariable

Constructor	Description
LinearInterpolatedTimeDiscreteProcess(Map<Double,RandomVariable> realizations)	Create a time discrete process by linear interpolation of random variables.

Uses of RandomVariable in net.finmath.montecarlo.process.component.barrier

Methods in net.finmath.montecarlo.process.component.barrier that return RandomVariable

Modifier and Type	Method	Description
RandomVariable	Barrier.getBarrierLevel(int timeIndex, RandomVariable[] randomVariable)	The barrier level

Methods in net.finmath.montecarlo.process.component.barrier with parameters of type RandomVariable

Modifier and Type	Method	Description
RandomVariableFromDoubleArray[]	Barrier.getBarrierDirection(int timeIndex, RandomVariable[] randomVariable)	The barrier direction, i.e. a (stochastic) projection vector for the components)
RandomVariable	Barrier.getBarrierLevel(int timeIndex, RandomVariable[] randomVariable)	The barrier level

Uses of RandomVariable in net.finmath.montecarlo.process.component.factordrift

Methods in net.finmath.montecarlo.process.component.factordrift that return RandomVariable

Modifier and Type	Method	Description
RandomVariable[]	FactorDrift.getFactorDrift(int timeIndex, RandomVariable[] realizationPredictor)	The interface describes how an additional factor drift may be specified for the generation of a process (see e.g.
RandomVariable	FactorDrift.getFactorDriftDeterminant(int timeIndex, RandomVariable[] realizationPredictor)	The interface describes how an additional factor drift may be specified for the generation of a process (see e.g.
RandomVariable[]	FactorDrift.getFactorScaling(int timeIndex, RandomVariable[] realizationPredictor)	The interface describes how an additional factor scaling may be specified for the generation of a process (see e.g.

Methods in net.finmath.montecarlo.process.component.factordrift with parameters of type RandomVariable

Modifier and Type	Method	Description
RandomVariable[]	FactorDrift.getFactorDrift(int timeIndex, RandomVariable[] realizationPredictor)	The interface describes how an additional factor drift may be specified for the generation of a process (see e.g.
RandomVariable	FactorDrift.getFactorDriftDeterminant(int timeIndex, RandomVariable[] realizationPredictor)	The interface describes how an additional factor drift may be specified for the generation of a process (see e.g.
RandomVariable[]	FactorDrift.getFactorScaling(int timeIndex, RandomVariable[] realizationPredictor)	The interface describes how an additional factor scaling may be specified for the generation of a process (see e.g.

Uses of RandomVariable in net.finmath.montecarlo.products

Methods in net.finmath.montecarlo.products that return RandomVariable

Modifier and Type	Method	Description
RandomVariable	PortfolioMonteCarloProduct.getValue(double evaluationTime, MonteCarloSimulationModel model)

Uses of RandomVariable in net.finmath.montecarlo.templatemethoddesign

Methods in net.finmath.montecarlo.templatemethoddesign that return RandomVariable

Modifier and Type	Method	Description
abstract RandomVariable	LogNormalProcess.getDrift(int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	LogNormalProcess.getDrift(int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)	Get the the drift.
abstract RandomVariable	LogNormalProcess.getFactorLoading(int timeIndex, int factor, int component, RandomVariable[] realizationAtTimeIndex)	This method should be overwritten and return the factor loading, i.e.
abstract RandomVariable[]	LogNormalProcess.getInitialValue()
RandomVariable	LogNormalProcess.getMonteCarloWeights(int timeIndex)	This method returns the weights of a weighted Monte Carlo method (the probability density).
RandomVariable[]	LogNormalProcess.getProcessValue(int timeIndex)	This method returns the realization of the process at a certain time index.
RandomVariable	LogNormalProcess.getProcessValue(int timeIndex, int componentIndex)	This method returns the realization of the process at a certain time index.

Methods in net.finmath.montecarlo.templatemethoddesign with parameters of type RandomVariable

Modifier and Type	Method	Description
abstract RandomVariable	LogNormalProcess.getDrift(int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable[]	LogNormalProcess.getDrift(int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)	Get the the drift.
abstract RandomVariable	LogNormalProcess.getFactorLoading(int timeIndex, int factor, int component, RandomVariable[] realizationAtTimeIndex)	This method should be overwritten and return the factor loading, i.e.

Uses of RandomVariable in net.finmath.montecarlo.templatemethoddesign.assetderivativevaluation

Methods in net.finmath.montecarlo.templatemethoddesign.assetderivativevaluation that return RandomVariable

Modifier and Type	Method	Description
RandomVariable	MonteCarloBlackScholesModel2.getAssetValue(double time, int assetIndex)
RandomVariable	MonteCarloBlackScholesModel2.getAssetValue(int timeIndex, int assetIndex)
RandomVariable	MonteCarloBlackScholesModel2.getDrift(int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable	MonteCarloBlackScholesModel2.getFactorLoading(int timeIndex, int factor, int component, RandomVariable[] realizationAtTimeIndex)
RandomVariable[]	MonteCarloBlackScholesModel2.getInitialValue()
RandomVariable	MonteCarloBlackScholesModel2.getMonteCarloWeights(double time)
RandomVariable	MonteCarloBlackScholesModel2.getNumeraire(double time)
RandomVariable	MonteCarloBlackScholesModel2.getNumeraire(int timeIndex)
RandomVariable	MonteCarloBlackScholesModel2.getRandomVariableForConstant(double value)

Methods in net.finmath.montecarlo.templatemethoddesign.assetderivativevaluation with parameters of type RandomVariable

Modifier and Type	Method	Description
RandomVariable	MonteCarloBlackScholesModel2.getDrift(int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
RandomVariable	MonteCarloBlackScholesModel2.getFactorLoading(int timeIndex, int factor, int component, RandomVariable[] realizationAtTimeIndex)

Uses of RandomVariable in net.finmath.optimizer

Methods in net.finmath.optimizer that return RandomVariable

Modifier and Type	Method	Description
RandomVariable[]	StochasticLevenbergMarquardt.getBestFitParameters()
RandomVariable[]	StochasticOptimizer.getBestFitParameters()	Get the best fit parameter vector.
RandomVariable[]	StochasticPathwiseLevenbergMarquardt.getBestFitParameters()
RandomVariable	StochasticPathwiseLevenbergMarquardt.getMeanSquaredError(RandomVariable[] value)

Methods in net.finmath.optimizer with parameters of type RandomVariable

Modifier and Type	Method	Description
StochasticLevenbergMarquardt	StochasticLevenbergMarquardt.getCloneWithModifiedTargetValues(RandomVariable[] newTargetVaues, RandomVariable[] newWeights, boolean isUseBestParametersAsInitialParameters)	Create a clone of this LevenbergMarquardt optimizer with a new vector for the target values and weights.
StochasticPathwiseLevenbergMarquardt	StochasticPathwiseLevenbergMarquardt.getCloneWithModifiedTargetValues(RandomVariable[] newTargetVaues, RandomVariable[] newWeights, boolean isUseBestParametersAsInitialParameters)	Create a clone of this LevenbergMarquardt optimizer with a new vector for the target values and weights.
double	StochasticLevenbergMarquardt.getMeanSquaredError(RandomVariable[] value)
RandomVariable	StochasticPathwiseLevenbergMarquardt.getMeanSquaredError(RandomVariable[] value)
default StochasticOptimizer	StochasticOptimizerFactory.getOptimizer(StochasticOptimizer.ObjectiveFunction objectiveFunction, RandomVariable[] initialParameters, RandomVariable[] targetValues)
default StochasticOptimizer	StochasticOptimizerFactory.getOptimizer(StochasticOptimizer.ObjectiveFunction objectiveFunction, RandomVariable[] initialParameters, RandomVariable[] lowerBound, RandomVariable[] upperBound, RandomVariable[] targetValues)
StochasticOptimizer	StochasticOptimizerFactory.getOptimizer(StochasticOptimizer.ObjectiveFunction objectiveFunction, RandomVariable[] initialParameters, RandomVariable[] lowerBound, RandomVariable[] upperBound, RandomVariable[] parameterStep, RandomVariable[] targetValues)
StochasticOptimizer	StochasticOptimizerFactoryLevenbergMarquardt.getOptimizer(StochasticOptimizer.ObjectiveFunction objectiveFunction, RandomVariable[] initialParameters, RandomVariable[] lowerBound, RandomVariable[] upperBound, RandomVariable[] parameterSteps, RandomVariable[] targetValues)
StochasticOptimizer	StochasticOptimizerFactoryLevenbergMarquardtAD.getOptimizer(StochasticOptimizer.ObjectiveFunction objectiveFunction, RandomVariable[] initialParameters, RandomVariable[] lowerBound, RandomVariable[] upperBound, RandomVariable[] parameterSteps, RandomVariable[] targetValues)
StochasticOptimizer	StochasticOptimizerFactoryPathwiseLevenbergMarquardtAD.getOptimizer(StochasticOptimizer.ObjectiveFunction objectiveFunction, RandomVariable[] initialParameters, RandomVariable[] targetValues)
StochasticOptimizer	StochasticOptimizerFactoryPathwiseLevenbergMarquardtAD.getOptimizer(StochasticOptimizer.ObjectiveFunction objectiveFunction, RandomVariable[] initialParameters, RandomVariable[] lowerBound, RandomVariable[] upperBound, RandomVariable[] targetValues)
StochasticOptimizer	StochasticOptimizerFactoryPathwiseLevenbergMarquardtAD.getOptimizer(StochasticOptimizer.ObjectiveFunction objectiveFunction, RandomVariable[] initialParameters, RandomVariable[] lowerBound, RandomVariable[] upperBound, RandomVariable[] parameterSteps, RandomVariable[] targetValues)
StochasticOptimizer	StochasticPathwiseOptimizerFactoryLevenbergMarquardt.getOptimizer(StochasticOptimizer.ObjectiveFunction objectiveFunction, RandomVariable[] initialParameters, RandomVariable[] targetValues)
StochasticOptimizer	StochasticPathwiseOptimizerFactoryLevenbergMarquardt.getOptimizer(StochasticOptimizer.ObjectiveFunction objectiveFunction, RandomVariable[] initialParameters, RandomVariable[] lowerBound, RandomVariable[] upperBound, RandomVariable[] targetValues)
StochasticOptimizer	StochasticPathwiseOptimizerFactoryLevenbergMarquardt.getOptimizer(StochasticOptimizer.ObjectiveFunction objectiveFunction, RandomVariable[] initialParameters, RandomVariable[] lowerBound, RandomVariable[] upperBound, RandomVariable[] parameterSteps, RandomVariable[] targetValues)
protected void	StochasticLevenbergMarquardt.prepareAndSetDerivatives(RandomVariable[] parameters, RandomVariable[] values, RandomVariable[][] derivatives)
protected void	StochasticLevenbergMarquardtAD.prepareAndSetDerivatives(RandomVariable[] parameters, RandomVariable[] values, RandomVariable[][] derivatives)
protected void	StochasticPathwiseLevenbergMarquardt.prepareAndSetDerivatives(RandomVariable[] parameters, RandomVariable[] values, RandomVariable[][] derivatives)
protected void	StochasticPathwiseLevenbergMarquardtAD.prepareAndSetDerivatives(RandomVariable[] parameters, RandomVariable[] values, RandomVariable[][] derivatives)
protected void	StochasticLevenbergMarquardt.prepareAndSetValues(RandomVariable[] parameters, RandomVariable[] values)
protected void	StochasticLevenbergMarquardtAD.prepareAndSetValues(RandomVariable[] parameters, RandomVariable[] values)
protected void	StochasticPathwiseLevenbergMarquardt.prepareAndSetValues(RandomVariable[] parameters, RandomVariable[] values)
protected void	StochasticPathwiseLevenbergMarquardtAD.prepareAndSetValues(RandomVariable[] parameters, RandomVariable[] values)
void	StochasticLevenbergMarquardt.setDerivatives(RandomVariable[] parameters, RandomVariable[][] derivatives)	The derivative of the objective function.
void	StochasticPathwiseLevenbergMarquardt.setDerivatives(RandomVariable[] parameters, RandomVariable[][] derivatives)	The derivative of the objective function.
void	StochasticPathwiseLevenbergMarquardt.setErrorMeanSquaredCurrent(RandomVariable errorMeanSquaredCurrent)
abstract void	StochasticLevenbergMarquardt.setValues(RandomVariable[] parameters, RandomVariable[] values)	The objective function.
void	StochasticOptimizer.ObjectiveFunction.setValues(RandomVariable[] parameters, RandomVariable[] values)
abstract void	StochasticPathwiseLevenbergMarquardt.setValues(RandomVariable[] parameters, RandomVariable[] values)	The objective function.

Method parameters in net.finmath.optimizer with type arguments of type RandomVariable

Modifier and Type	Method	Description
StochasticLevenbergMarquardt	StochasticLevenbergMarquardt.getCloneWithModifiedTargetValues(List<RandomVariable> newTargetVaues, List<RandomVariable> newWeights, boolean isUseBestParametersAsInitialParameters)	Create a clone of this LevenbergMarquardt optimizer with a new vector for the target values and weights.
StochasticPathwiseLevenbergMarquardt	StochasticPathwiseLevenbergMarquardt.getCloneWithModifiedTargetValues(List<RandomVariable> newTargetVaues, List<RandomVariable> newWeights, boolean isUseBestParametersAsInitialParameters)	Create a clone of this LevenbergMarquardt optimizer with a new vector for the target values and weights.

Constructors in net.finmath.optimizer with parameters of type RandomVariable

Constructor	Description
StochasticLevenbergMarquardt(StochasticLevenbergMarquardt.RegularizationMethod regularizationMethod, RandomVariable[] initialParameters, RandomVariable[] targetValues, RandomVariable[] parameterSteps, int maxIteration, double errorTolerance, int numberOfThreads)	Create a Levenberg-Marquardt solver.
StochasticLevenbergMarquardt(StochasticLevenbergMarquardt.RegularizationMethod regularizationMethod, RandomVariable[] initialParameters, RandomVariable[] targetValues, RandomVariable[] parameterSteps, int maxIteration, double errorTolerance, ExecutorService executorService)	Create a Levenberg-Marquardt solver.
StochasticLevenbergMarquardt(RandomVariable[] initialParameters, RandomVariable[] targetValues, RandomVariable[] parameterSteps, int maxIteration, double errorTolerance, ExecutorService executorService)	Create a Levenberg-Marquardt solver.
StochasticLevenbergMarquardtAD(StochasticLevenbergMarquardt.RegularizationMethod regularizationMethod, RandomVariable[] initialParameters, RandomVariable[] targetValues, RandomVariable[] parameterSteps, int maxIteration, double errorTolerance, ExecutorService executorService)
StochasticLevenbergMarquardtAD(StochasticLevenbergMarquardt.RegularizationMethod regularizationMethod, RandomVariable[] initialParameters, RandomVariable[] targetValues, RandomVariable[] parameterSteps, int maxIteration, double errorTolerance, ExecutorService executorService, boolean isGradientValuationParallel)
StochasticOptimizerFactoryPathwiseLevenbergMarquardtAD(int maxIterations, RandomVariable errorTolerance, int maxThreads)
StochasticPathwiseLevenbergMarquardt(RandomVariable[] initialParameters, RandomVariable[] targetValues, int maxIteration, int numberOfThreads)	Create a Levenberg-Marquardt solver.
StochasticPathwiseLevenbergMarquardt(RandomVariable[] initialParameters, RandomVariable[] targetValues, RandomVariable[] weights, RandomVariable[] parameterSteps, int maxIteration, RandomVariable errorTolerance, ExecutorService executorService)	Create a Levenberg-Marquardt solver.
StochasticPathwiseLevenbergMarquardtAD(RandomVariable[] initialParameters, RandomVariable[] targetValues, int maxIteration, int numberOfThreads)
StochasticPathwiseLevenbergMarquardtAD(RandomVariable[] initialParameters, RandomVariable[] targetValues, RandomVariable[] weights, RandomVariable[] parameterSteps, int maxIteration, RandomVariable errorTolerance, ExecutorService executorService)

Constructor parameters in net.finmath.optimizer with type arguments of type RandomVariable

Constructor	Description
StochasticPathwiseLevenbergMarquardt(List<RandomVariable> initialParameters, List<RandomVariable> targetValues, int maxIteration, int numberOfThreads)	Create a Levenberg-Marquardt solver.
StochasticPathwiseLevenbergMarquardt(List<RandomVariable> initialParameters, List<RandomVariable> targetValues, int maxIteration, ExecutorService executorService)	Create a Levenberg-Marquardt solver.
StochasticPathwiseLevenbergMarquardtAD(List<RandomVariable> initialParameters, List<RandomVariable> targetValues, int maxIteration, int numberOfThreads)
StochasticPathwiseLevenbergMarquardtAD(List<RandomVariable> initialParameters, List<RandomVariable> targetValues, int maxIteration, ExecutorService executorService)

Uses of RandomVariable in net.finmath.stochastic

Subinterfaces of RandomVariable in net.finmath.stochastic

Modifier and Type	Interface	Description
interface	RandomVariableAccumulator	The interface implemented by a mutable random variable accumulator.
interface	RandomVariableArray	An array of RandomVariable objects, implementing the RandomVariable interface.

Classes in net.finmath.stochastic that implement RandomVariable

Modifier and Type	Class	Description
class	RandomVariableArrayImplementation	An implementation of RandomVariableArray implementing an array of RandomVariable objects, implementing the RandomVariable interface.
class	Scalar	A scalar value implementing the RandomVariable.

Methods in net.finmath.stochastic that return RandomVariable

Modifier and Type	Method	Description
RandomVariable	RandomVariable.abs()	Applies x → Math.abs(x), i.e. x → |x| to this random variable.
RandomVariable	RandomVariableArrayImplementation.abs()
RandomVariable	Scalar.abs()
RandomVariable	RandomVariable.accrue(RandomVariable rate, double periodLength)	Applies x → x * (1.0 + rate * periodLength) to this random variable.
RandomVariable	RandomVariableArrayImplementation.accrue(RandomVariable rate, double periodLength)
RandomVariable	Scalar.accrue(RandomVariable rate, double periodLength)
RandomVariable	RandomVariable.add(double value)	Applies x → x + value to this random variable.
RandomVariable	RandomVariable.add(RandomVariable randomVariable)	Applies x → x+randomVariable to this random variable.
RandomVariable	RandomVariableArrayImplementation.add(double value)
RandomVariable	RandomVariableArrayImplementation.add(RandomVariable randomVariable)
RandomVariable	Scalar.add(double value)
RandomVariable	Scalar.add(RandomVariable randomVariable)
RandomVariable	RandomVariable.addProduct(RandomVariable factor1, double factor2)	Applies x → x + factor1 * factor2
RandomVariable	RandomVariable.addProduct(RandomVariable factor1, RandomVariable factor2)	Applies x → x + factor1 * factor2
RandomVariable	RandomVariableArrayImplementation.addProduct(RandomVariable factor1, double factor2)
RandomVariable	RandomVariableArrayImplementation.addProduct(RandomVariable factor1, RandomVariable factor2)
RandomVariable	Scalar.addProduct(RandomVariable factor1, double factor2)
RandomVariable	Scalar.addProduct(RandomVariable factor1, RandomVariable factor2)
RandomVariable	RandomVariable.addRatio(RandomVariable numerator, RandomVariable denominator)	Applies x → x + numerator / denominator
RandomVariable	RandomVariableArrayImplementation.addRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	Scalar.addRatio(RandomVariable numerator, RandomVariable denominator)
default RandomVariable	RandomVariable.addSumProduct(List<RandomVariable> factor1, List<RandomVariable> factor2)	Applies \( x \mapsto x + \sum_{i=0}^{n-1} factor1_{i} * factor2_{i}
default RandomVariable	RandomVariable.addSumProduct(RandomVariable[] factor1, RandomVariable[] factor2)	Applies \( x \mapsto x + \sum_{i=0}^{n-1} factor1_{i} * factor2_{i}
RandomVariable	RandomOperator.apply(RandomVariable value)	Applies this function to the given argument.
RandomVariable	RandomVariable.apply(DoubleBinaryOperator operator, RandomVariable argument)	Applies x → operator(x,y) to this random variable, where x is this random variable and y is a given random variable.
RandomVariable	RandomVariable.apply(DoubleUnaryOperator operator)	Applies x → operator(x) to this random variable.
RandomVariable	RandomVariable.apply(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2)	Applies x → operator(x,y,z) to this random variable, where x is this random variable and y and z are given random variable.
RandomVariable	RandomVariableArrayImplementation.apply(DoubleBinaryOperator operator, RandomVariable argument)
RandomVariable	RandomVariableArrayImplementation.apply(DoubleUnaryOperator operator)
RandomVariable	RandomVariableArrayImplementation.apply(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2)
RandomVariable	Scalar.apply(DoubleBinaryOperator operator, RandomVariable argument)
RandomVariable	Scalar.apply(DoubleUnaryOperator operator)
RandomVariable	Scalar.apply(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2)
default RandomVariable	RandomVariable.appy(RandomOperator operator)	Applies x → operator(x) to this random variable.
RandomVariable	RandomVariable.average()	Returns a random variable which is deterministic and corresponds the expectation of this random variable.
RandomVariable	RandomVariableArrayImplementation.average()
RandomVariable	Scalar.average()
RandomVariable	RandomVariable.bus(RandomVariable randomVariable)	Applies x → randomVariable-x to this random variable.
RandomVariable	RandomVariableArrayImplementation.bus(RandomVariable randomVariable)
RandomVariable	Scalar.bus(RandomVariable randomVariable)
RandomVariable	RandomVariable.cache()	Return a cacheable version of this object (often a self-reference).
RandomVariable	RandomVariableArrayImplementation.cache()
RandomVariable	Scalar.cache()
RandomVariable	RandomVariable.cap(double cap)	Applies x → min(x,cap) to this random variable.
RandomVariable	RandomVariable.cap(RandomVariable cap)	Applies x → min(x,cap) to this random variable.
RandomVariable	RandomVariableArrayImplementation.cap(double cap)
RandomVariable	RandomVariableArrayImplementation.cap(RandomVariable cap)
RandomVariable	Scalar.cap(double cap)
RandomVariable	Scalar.cap(RandomVariable cap)
RandomVariable	RandomVariable.choose(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative)	Applies x → (x ≥ 0 ?
RandomVariable	RandomVariableArrayImplementation.choose(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative)
RandomVariable	Scalar.choose(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative)
RandomVariable	RandomVariable.cos()	Applies x → cos(x) to this random variable.
RandomVariable	RandomVariableArrayImplementation.cos()
RandomVariable	Scalar.cos()
RandomVariable	RandomVariable.discount(RandomVariable rate, double periodLength)	Applies x → x / (1.0 + rate * periodLength) to this random variable.
RandomVariable	RandomVariableArrayImplementation.discount(RandomVariable rate, double periodLength)
RandomVariable	Scalar.discount(RandomVariable rate, double periodLength)
RandomVariable	RandomVariable.div(double value)	Applies x → x / value to this random variable.
RandomVariable	RandomVariable.div(RandomVariable randomVariable)	Applies x → x/randomVariable to this random variable.
RandomVariable	RandomVariableArrayImplementation.div(double value)
RandomVariable	RandomVariableArrayImplementation.div(RandomVariable randomVariable)
RandomVariable	Scalar.div(double value)
RandomVariable	Scalar.div(RandomVariable randomVariable)
RandomVariable	RandomVariable.exp()	Applies x → exp(x) to this random variable.
RandomVariable	RandomVariableArrayImplementation.exp()
RandomVariable	Scalar.exp()
default RandomVariable	RandomVariable.expm1()	Applies x → expm1(x) (that is x → exp(x)-1.0) to this random variable.
RandomVariable	Scalar.expm1()
RandomVariable	RandomVariable.floor(double floor)	Applies x → max(x,floor) to this random variable.
RandomVariable	RandomVariable.floor(RandomVariable floor)	Applies x → max(x,floor) to this random variable.
RandomVariable	RandomVariableArrayImplementation.floor(double floor)
RandomVariable	RandomVariableArrayImplementation.floor(RandomVariable floor)
RandomVariable	Scalar.floor(double floor)
RandomVariable	Scalar.floor(RandomVariable floor)
RandomVariable	RandomVariableAccumulator.get()
RandomVariable	RandomVariableAccumulator.get(double fromTime, double toTime)
RandomVariable	ConditionalExpectationEstimator.getConditionalExpectation(RandomVariable randomVariable)	Return the conditional expectation of a given random variable.
default RandomVariable	RandomVariable.getConditionalExpectation(ConditionalExpectationEstimator conditionalExpectationOperator)	Returns the conditional expectation using a given conditional expectation estimator.
RandomVariable	RandomVariableArray.getElement(int index)
RandomVariable	RandomVariableArrayImplementation.getElement(int index)
default RandomVariable	RandomVariable.getValues()	Returns the underlying values and a random variable.
RandomVariable	RandomVariable.invert()	Applies x → 1/x to this random variable.
RandomVariable	RandomVariableArrayImplementation.invert()
RandomVariable	Scalar.invert()
RandomVariable	RandomVariable.isNaN()	Applies x → (Double.isNaN(x) ?
RandomVariable	RandomVariableArrayImplementation.isNaN()
RandomVariable	Scalar.isNaN()
RandomVariable	RandomVariable.log()	Applies x → log(x) to this random variable.
RandomVariable	RandomVariableArrayImplementation.log()
RandomVariable	Scalar.log()
RandomVariable	RandomVariable.mult(double value)	Applies x → x * value to this random variable.
RandomVariable	RandomVariable.mult(RandomVariable randomVariable)	Applies x → x*randomVariable to this random variable.
RandomVariable	RandomVariableArrayImplementation.mult(double value)
RandomVariable	RandomVariableArrayImplementation.mult(RandomVariable randomVariable)
RandomVariable	Scalar.mult(double value)
RandomVariable	Scalar.mult(RandomVariable randomVariable)
RandomVariable	RandomVariable.pow(double exponent)	Applies x → pow(x,exponent) to this random variable.
RandomVariable	RandomVariableArrayImplementation.pow(double exponent)
RandomVariable	Scalar.pow(double exponent)
RandomVariable	RandomVariable.sin()	Applies x → sin(x) to this random variable.
RandomVariable	RandomVariableArrayImplementation.sin()
RandomVariable	Scalar.sin()
RandomVariable	RandomVariable.sqrt()	Applies x → sqrt(x) to this random variable.
RandomVariable	RandomVariableArrayImplementation.sqrt()
RandomVariable	Scalar.sqrt()
RandomVariable	RandomVariable.squared()	Applies x → x * x to this random variable.
RandomVariable	RandomVariableArrayImplementation.squared()
RandomVariable	Scalar.squared()
RandomVariable	RandomVariable.sub(double value)	Applies x → x - value to this random variable.
RandomVariable	RandomVariable.sub(RandomVariable randomVariable)	Applies x → x-randomVariable to this random variable.
RandomVariable	RandomVariableArrayImplementation.sub(double value)
RandomVariable	RandomVariableArrayImplementation.sub(RandomVariable randomVariable)
RandomVariable	Scalar.sub(double value)
RandomVariable	Scalar.sub(RandomVariable randomVariable)
RandomVariable	RandomVariable.subRatio(RandomVariable numerator, RandomVariable denominator)	Applies x → x - numerator / denominator
RandomVariable	RandomVariableArrayImplementation.subRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	Scalar.subRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	RandomVariableArray.sumProduct(RandomVariableArray array)	Components wise product followed by sum of all elements.
RandomVariable	RandomVariableArrayImplementation.sumProduct(RandomVariableArray array)
RandomVariable	RandomVariable.vid(RandomVariable randomVariable)	Applies x → randomVariable/x to this random variable.
RandomVariable	RandomVariableArrayImplementation.vid(RandomVariable randomVariable)
RandomVariable	Scalar.vid(RandomVariable randomVariable)

Methods in net.finmath.stochastic with parameters of type RandomVariable

Modifier and Type	Method	Description
RandomVariable	RandomVariable.accrue(RandomVariable rate, double periodLength)	Applies x → x * (1.0 + rate * periodLength) to this random variable.
RandomVariable	RandomVariableArrayImplementation.accrue(RandomVariable rate, double periodLength)
RandomVariable	Scalar.accrue(RandomVariable rate, double periodLength)
void	RandomVariableAccumulator.accumulate(double time, RandomVariable randomVariable)
void	RandomVariableAccumulator.accumulate(RandomVariable randomVariable)
RandomVariable	RandomVariable.add(RandomVariable randomVariable)	Applies x → x+randomVariable to this random variable.
RandomVariable	RandomVariableArrayImplementation.add(RandomVariable randomVariable)
RandomVariable	Scalar.add(RandomVariable randomVariable)
RandomVariable	RandomVariable.addProduct(RandomVariable factor1, double factor2)	Applies x → x + factor1 * factor2
RandomVariable	RandomVariable.addProduct(RandomVariable factor1, RandomVariable factor2)	Applies x → x + factor1 * factor2
RandomVariable	RandomVariableArrayImplementation.addProduct(RandomVariable factor1, double factor2)
RandomVariable	RandomVariableArrayImplementation.addProduct(RandomVariable factor1, RandomVariable factor2)
RandomVariable	Scalar.addProduct(RandomVariable factor1, double factor2)
RandomVariable	Scalar.addProduct(RandomVariable factor1, RandomVariable factor2)
RandomVariable	RandomVariable.addRatio(RandomVariable numerator, RandomVariable denominator)	Applies x → x + numerator / denominator
RandomVariable	RandomVariableArrayImplementation.addRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	Scalar.addRatio(RandomVariable numerator, RandomVariable denominator)
default RandomVariable	RandomVariable.addSumProduct(RandomVariable[] factor1, RandomVariable[] factor2)	Applies \( x \mapsto x + \sum_{i=0}^{n-1} factor1_{i} * factor2_{i}
RandomVariable	RandomOperator.apply(RandomVariable value)	Applies this function to the given argument.
RandomVariable	RandomVariable.apply(DoubleBinaryOperator operator, RandomVariable argument)	Applies x → operator(x,y) to this random variable, where x is this random variable and y is a given random variable.
RandomVariable	RandomVariable.apply(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2)	Applies x → operator(x,y,z) to this random variable, where x is this random variable and y and z are given random variable.
RandomVariable	RandomVariableArrayImplementation.apply(DoubleBinaryOperator operator, RandomVariable argument)
RandomVariable	RandomVariableArrayImplementation.apply(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2)
RandomVariable	Scalar.apply(DoubleBinaryOperator operator, RandomVariable argument)
RandomVariable	Scalar.apply(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2)
RandomVariable	RandomVariable.bus(RandomVariable randomVariable)	Applies x → randomVariable-x to this random variable.
RandomVariable	RandomVariableArrayImplementation.bus(RandomVariable randomVariable)
RandomVariable	Scalar.bus(RandomVariable randomVariable)
RandomVariable	RandomVariable.cap(RandomVariable cap)	Applies x → min(x,cap) to this random variable.
RandomVariable	RandomVariableArrayImplementation.cap(RandomVariable cap)
RandomVariable	Scalar.cap(RandomVariable cap)
RandomVariable	RandomVariable.choose(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative)	Applies x → (x ≥ 0 ?
RandomVariable	RandomVariableArrayImplementation.choose(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative)
RandomVariable	Scalar.choose(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative)
RandomVariable	RandomVariable.discount(RandomVariable rate, double periodLength)	Applies x → x / (1.0 + rate * periodLength) to this random variable.
RandomVariable	RandomVariableArrayImplementation.discount(RandomVariable rate, double periodLength)
RandomVariable	Scalar.discount(RandomVariable rate, double periodLength)
RandomVariable	RandomVariable.div(RandomVariable randomVariable)	Applies x → x/randomVariable to this random variable.
RandomVariable	RandomVariableArrayImplementation.div(RandomVariable randomVariable)
RandomVariable	Scalar.div(RandomVariable randomVariable)
boolean	RandomVariable.equals(RandomVariable randomVariable)	Compare this random variable with a given one
boolean	RandomVariableArrayImplementation.equals(RandomVariable randomVariable)
boolean	Scalar.equals(RandomVariable randomVariable)
RandomVariable	RandomVariable.floor(RandomVariable floor)	Applies x → max(x,floor) to this random variable.
RandomVariable	RandomVariableArrayImplementation.floor(RandomVariable floor)
RandomVariable	Scalar.floor(RandomVariable floor)
double	RandomVariable.getAverage(RandomVariable probabilities)	Returns the expectation of this random variable for a given probability measure (weight).
double	RandomVariableArrayImplementation.getAverage(RandomVariable probabilities)
double	Scalar.getAverage(RandomVariable probabilities)
RandomVariable	ConditionalExpectationEstimator.getConditionalExpectation(RandomVariable randomVariable)	Return the conditional expectation of a given random variable.
double	RandomVariable.getQuantile(double quantile, RandomVariable probabilities)	Returns the quantile value for this given random variable, i.e., the value x such that P(this < x) = quantile, where P denotes the probability measure.
double	RandomVariableArrayImplementation.getQuantile(double quantile, RandomVariable probabilities)
double	Scalar.getQuantile(double quantile, RandomVariable probabilities)
double	RandomVariable.getStandardDeviation(RandomVariable probabilities)	Returns the standard deviation of this random variable, i.e., sqrt(V) where V = ((X-m)^2).getAverage(probabilities) and X = this and m = X.getAverage(probabilities).
double	RandomVariableArrayImplementation.getStandardDeviation(RandomVariable probabilities)
double	Scalar.getStandardDeviation(RandomVariable probabilities)
double	RandomVariable.getStandardError(RandomVariable probabilities)	Returns the standard error (discretization error) of this random variable.
double	RandomVariableArrayImplementation.getStandardError(RandomVariable probabilities)
double	Scalar.getStandardError(RandomVariable probabilities)
double	RandomVariable.getVariance(RandomVariable probabilities)	Returns the variance of this random variable, i.e., V where V = ((X-m)^2).getAverage(probabilities) and X = this and m = X.getAverage(probabilities).
double	RandomVariableArrayImplementation.getVariance(RandomVariable probabilities)
double	Scalar.getVariance(RandomVariable probabilities)
RandomVariable	RandomVariable.mult(RandomVariable randomVariable)	Applies x → x*randomVariable to this random variable.
RandomVariable	RandomVariableArrayImplementation.mult(RandomVariable randomVariable)
RandomVariable	Scalar.mult(RandomVariable randomVariable)
static RandomVariableArray	RandomVariableArrayImplementation.of(RandomVariable[] elements)
RandomVariable	RandomVariable.sub(RandomVariable randomVariable)	Applies x → x-randomVariable to this random variable.
RandomVariable	RandomVariableArrayImplementation.sub(RandomVariable randomVariable)
RandomVariable	Scalar.sub(RandomVariable randomVariable)
RandomVariable	RandomVariable.subRatio(RandomVariable numerator, RandomVariable denominator)	Applies x → x - numerator / denominator
RandomVariable	RandomVariableArrayImplementation.subRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	Scalar.subRatio(RandomVariable numerator, RandomVariable denominator)
RandomVariable	RandomVariable.vid(RandomVariable randomVariable)	Applies x → randomVariable/x to this random variable.
RandomVariable	RandomVariableArrayImplementation.vid(RandomVariable randomVariable)
RandomVariable	Scalar.vid(RandomVariable randomVariable)

Method parameters in net.finmath.stochastic with type arguments of type RandomVariable

Modifier and Type	Method	Description
default RandomVariable	RandomVariable.addSumProduct(List<RandomVariable> factor1, List<RandomVariable> factor2)	Applies \( x \mapsto x + \sum_{i=0}^{n-1} factor1_{i} * factor2_{i}