Uses of Interface
net.finmath.montecarlo.process.Process

Packages that use Process

Package	Description
net.finmath.montecarlo.process	Interfaced for stochastic processes and numerical schemes for stochastic processes (SDEs), like the Euler scheme.

Uses of Process in net.finmath.montecarlo.process

Subinterfaces of Process in net.finmath.montecarlo.process

Modifier and Type	Interface	Description
interface	MonteCarloProcess	The interface for a process (numerical scheme) of a stochastic process X where X = f(Y) and Y is an Itô process \[ dY_{j} = \mu_{j} dt + \lambda_{1,j} dW_{1} + \ldots + \lambda_{m,j} dW_{m} \] The parameters are provided by a model implementing ProcessModel: The value of Y(0) is provided by the method ProcessModel.getInitialState(net.finmath.montecarlo.process.MonteCarloProcess).

Classes in net.finmath.montecarlo.process that implement Process

Modifier and Type	Class	Description
class	EulerSchemeFromProcessModel	This class implements some numerical schemes for multi-dimensional multi-factor Ito process.
class	LinearInterpolatedTimeDiscreteProcess	A linear interpolated time discrete process, that is, given a collection of tuples (Double, RandomVariable) representing realizations \( X(t_{i}) \) this class implements the Process and creates a stochastic process \( t \mapsto X(t) \) where \[ X(t) = \frac{t_{i+1} - t}{t_{i+1}-t_{i}} X(t_{i}) + \frac{t - t_{i}}{t_{i+1}-t_{i}} X(t_{i+1}) \] with \( t_{i} \leq t \leq t_{i+1} \).
class	MonteCarloProcessFromProcessModel	This class is an abstract base class to implement a multi-dimensional multi-factor Ito process.

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

Modifier and Type	Method	Description
Process	LinearInterpolatedTimeDiscreteProcess.clone()
Process	Process.clone()	Create and return a clone of this process.