java.lang.Object
- net.finmath.montecarlo.RandomVariableFromFloatArray

All Implemented Interfaces:

Serializable, RandomVariable
```
public class RandomVariableFromFloatArray
extends Object
implements RandomVariable
```
The class RandomVariableFromFloatArray represents a random variable being the evaluation of a stochastic process at a certain time within a Monte-Carlo simulation. It is thus essentially a vector of floating point numbers - the realizations - together with a double - the time. The index of the vector represents path. The class may also be used for non-stochastic quantities which may potentially be stochastic (e.g. volatility). If only non-stochastic random variables are involved in an operation the class uses optimized code. Accesses performed exclusively through the interface RandomVariable is thread safe (and does not mutate the class). This implementation uses floats for the realizations (consuming less memory compared to using doubles). However, the calculation of the average is performed using double precision.

Version:

1.8

Author:

Christian Fries

See Also:

Serialized Form

Constructor Summary

Constructors
Constructor	Description
`RandomVariableFromFloatArray(double value)`	Create a non stochastic random variable, i.e.
`RandomVariableFromFloatArray(double time, double value)`	Create a non stochastic random variable, i.e.
`RandomVariableFromFloatArray(double time, double[] realisations)`	Create a stochastic random variable.
`RandomVariableFromFloatArray(double time, double value, int typePriority)`	Create a non stochastic random variable, i.e.
`RandomVariableFromFloatArray(double time, float[] newRealizations)`	Create a non stochastic random variable, i.e.
`RandomVariableFromFloatArray(double time, float[] realisations, int typePriority)`	Create a stochastic random variable.
`RandomVariableFromFloatArray(double time, int numberOfPath, double value)`	Deprecated.
`RandomVariableFromFloatArray(double time, IntToDoubleFunction realizations, int size)`	Create a stochastic random variable.
`RandomVariableFromFloatArray(double time, IntToDoubleFunction realizations, int size, int typePriority)`	Create a stochastic random variable.
`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`.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`RandomVariable`	`abs()`	Applies x → Math.abs(x), i.e.
`RandomVariable`	`accrue(RandomVariable rate, double periodLength)`	Applies x → x * (1.0 + rate * periodLength) to this random variable.
`RandomVariable`	`add(double value)`	Applies x → x + value to this random variable.
`RandomVariable`	`add(RandomVariable randomVariable)`	Applies x → x+randomVariable to this random variable.
`RandomVariable`	`addProduct(RandomVariable factor1, double factor2)`	Applies x → x + factor1 * factor2
`RandomVariable`	`addProduct(RandomVariable factor1, RandomVariable factor2)`	Applies x → x + factor1 * factor2
`RandomVariable`	`addRatio(RandomVariable numerator, RandomVariable denominator)`	Applies x → x + numerator / denominator
`RandomVariable`	`addSumProduct(List<RandomVariable> factor1, List<RandomVariable> factor2)`	Applies \( x \mapsto x + \sum_{i=0}^{n-1} factor1_{i} * factor2_{i}
`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`	`apply(DoubleUnaryOperator operator)`	Applies x → operator(x) to this random variable.
`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`	`average()`	Returns a random variable which is deterministic and corresponds the expectation of this random variable.
`RandomVariable`	`bus(RandomVariable randomVariable)`	Applies x → randomVariable-x to this random variable.
`RandomVariable`	`cache()`	Return a cacheable version of this object (often a self-reference).
`RandomVariable`	`cap(double cap)`	Applies x → min(x,cap) to this random variable.
`RandomVariable`	`cap(RandomVariable randomVariable)`	Applies x → min(x,cap) to this random variable.
`RandomVariable`	`choose(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative)`	Applies x → (x ≥ 0 ? valueIfTriggerNonNegative : valueIfTriggerNegative)
`RandomVariable`	`cos()`	Applies x → cos(x) to this random variable.
`RandomVariable`	`discount(RandomVariable rate, double periodLength)`	Applies x → x / (1.0 + rate * periodLength) to this random variable.
`RandomVariable`	`div(double value)`	Applies x → x / value to this random variable.
`RandomVariable`	`div(RandomVariable randomVariable)`	Applies x → x/randomVariable to this random variable.
`Double`	`doubleValue()`	Returns the double value if isDeterministic() is true.
`boolean`	`equals(RandomVariable randomVariable)`	Compare this random variable with a given one
`RandomVariableFromFloatArray`	`exp()`	Applies x → exp(x) to this random variable.
`RandomVariable`	`floor(double floor)`	Applies x → max(x,floor) to this random variable.
`RandomVariable`	`floor(RandomVariable randomVariable)`	Applies x → max(x,floor) to this random variable.
`double`	`get(int pathOrState)`	Evaluate at a given path or state.
`double`	`getAverage()`	Returns the expectation of this random variable.
`double`	`getAverage(RandomVariable probabilities)`	Returns the expectation of this random variable for a given probability measure (weight).
`RandomVariable`	`getConditionalExpectation(ConditionalExpectationEstimator conditionalExpectationOperator)`	Returns the conditional expectation using a given conditional expectation estimator.
`double`	`getFiltrationTime()`	Returns the filtration time.
`double[]`	`getHistogram(double[] intervalPoints)`	Generates a Histogram based on the realizations stored in this random variable.
`double[][]`	`getHistogram(int numberOfPoints, double standardDeviations)`	Generates a histogram based on the realizations stored in this random variable using interval points calculated from the arguments, see also `RandomVariable.getHistogram(double[])`.
`double`	`getMax()`	Returns the maximum value attained by this random variable.
`double`	`getMin()`	Returns the minimum value attained by this random variable.
`IntToDoubleFunction`	`getOperator()`	Returns the operator path → this.get(path) corresponding to this random variable.
`double`	`getQuantile(double quantile)`	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`	`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`	`getQuantileExpectation(double quantileStart, double quantileEnd)`	Returns the expectation over a quantile for this given random variable.
`double[]`	`getRealizations()`	Returns a vector representing the realization of this random variable.
`DoubleStream`	`getRealizationsStream()`	Returns a stream of doubles corresponding to the realizations of this random variable.
`double`	`getSampleVariance()`	Returns the sample variance of this random variable, i.e., V * size()/(size()-1) where V = getVariance().
`double`	`getStandardDeviation()`	Returns the standard deviation of this random variable, i.e., sqrt(V) where V = ((X-m)^2).getAverage() and X = this and m = X.getAverage().
`double`	`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`	`getStandardError()`	Returns the standard error (discretization error) of this random variable.
`double`	`getStandardError(RandomVariable probabilities)`	Returns the standard error (discretization error) of this random variable.
`int`	`getTypePriority()`	Returns the type priority.
`double`	`getVariance()`	Returns the variance of this random variable, i.e., V where V = ((X-m)^2).getAverage() and X = this and m = X.getAverage().
`double`	`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).
`RandomVariable`	`invert()`	Applies x → 1/x to this random variable.
`boolean`	`isDeterministic()`	Check if this random variable is deterministic in the sense that it is represented by a single double value.
`RandomVariable`	`isNaN()`	Applies x → (Double.isNaN(x) ? 1.0 : 0.0)
`RandomVariableFromFloatArray`	`log()`	Applies x → log(x) to this random variable.
`RandomVariable`	`mult(double value)`	Applies x → x * value to this random variable.
`RandomVariable`	`mult(RandomVariable randomVariable)`	Applies x → x*randomVariable to this random variable.
`RandomVariable`	`pow(double exponent)`	Applies x → pow(x,exponent) to this random variable.
`RandomVariable`	`sin()`	Applies x → sin(x) to this random variable.
`int`	`size()`	Returns the number of paths or states.
`RandomVariable`	`sqrt()`	Applies x → sqrt(x) to this random variable.
`RandomVariable`	`squared()`	Applies x → x * x to this random variable.
`RandomVariable`	`sub(double value)`	Applies x → x - value to this random variable.
`RandomVariable`	`sub(RandomVariable randomVariable)`	Applies x → x-randomVariable to this random variable.
`RandomVariable`	`subRatio(RandomVariable numerator, RandomVariable denominator)`	Applies x → x - numerator / denominator
`String`	`toString()`
`RandomVariable`	`vid(RandomVariable randomVariable)`	Applies x → randomVariable/x to this random variable.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface net.finmath.stochastic.RandomVariable
addSumProduct, appy, expm1, getValues

- Constructor Detail
  - RandomVariableFromFloatArray
```
public RandomVariableFromFloatArray(RandomVariable value)
```
    Create a random variable from a given other implementation of RandomVariable.
    
    Parameters:
    
    value - Object implementing RandomVariable.
  - RandomVariableFromFloatArray
```
public RandomVariableFromFloatArray(double value)
```
    Create a non stochastic random variable, i.e. a constant.
    
    Parameters:
    
    value - the value, a constant.
  - RandomVariableFromFloatArray
```
public RandomVariableFromFloatArray(RandomVariable value,
                                    DoubleUnaryOperator function)
```
    Create a random variable by applying a function to a given other implementation of RandomVariable.
    
    Parameters:
    
    value - Object implementing RandomVariable.
    
    function - A function mapping double to double.
  - RandomVariableFromFloatArray
```
public RandomVariableFromFloatArray(double time,
                                    double value,
                                    int typePriority)
```
    Create a non stochastic random variable, i.e. a constant.
    
    Parameters:
    
    time - the filtration time, set to 0.0 if not used.
    
    value - the value, a constant.
    
    typePriority - The priority of this type in construction of result types. See "operator type priority" for details.
  - RandomVariableFromFloatArray
```
public RandomVariableFromFloatArray(double time,
                                    double value)
```
    Create a non stochastic random variable, i.e. a constant.
    
    Parameters:
    
    time - the filtration time, set to 0.0 if not used.
    
    value - the value, a constant.
  - RandomVariableFromFloatArray
```
public RandomVariableFromFloatArray(double time,
                                    float[] newRealizations)
```
    Create a non stochastic random variable, i.e. a constant.
    
    Parameters:
    
    time - the filtration time, set to 0.0 if not used.
    
    newRealizations - the value, a constant.
  - RandomVariableFromFloatArray
```
@Deprecated
public RandomVariableFromFloatArray(double time,
                                    int numberOfPath,
                                    double value)
```
    Deprecated.
    
    Create a non stochastic random variable, i.e. a constant.
    
    Parameters:
    
    time - the filtration time, set to 0.0 if not used.
    
    numberOfPath - The number of paths.
    
    value - the value, a constant.
  - RandomVariableFromFloatArray
```
public RandomVariableFromFloatArray(double time,
                                    float[] realisations,
                                    int typePriority)
```
    Create a stochastic random variable. Important: The realizations array is not cloned (no defensive copy is made).
    
    Parameters:
    
    time - the filtration time, set to 0.0 if not used.
    
    realisations - the vector of realizations.
    
    typePriority - The priority of this type in construction of result types. See "operator type priority" for details.
    
    To dos:
    
    A future version should perform a defensive copy.
  - RandomVariableFromFloatArray
```
public RandomVariableFromFloatArray(double time,
                                    double[] realisations)
```
    Create a stochastic random variable. Important: The realizations array is not cloned (not defensive copy is made).
    
    Parameters:
    
    time - the filtration time, set to 0.0 if not used.
    
    realisations - the vector of realizations.
    
    To dos:
    
    A future version should perform a defensive copy.
  - RandomVariableFromFloatArray
```
public RandomVariableFromFloatArray(double time,
                                    IntToDoubleFunction realizations,
                                    int size,
                                    int typePriority)
```
    Create a stochastic random variable.
    
    Parameters:
    
    time - the filtration time, set to 0.0 if not used.
    
    realizations - A map mapping integer (path or state) to double, representing this random variable.
    
    size - The size, i.e., number of paths.
    
    typePriority - The priority of this type in construction of result types. See "operator type priority" for details.
  - RandomVariableFromFloatArray
```
public RandomVariableFromFloatArray(double time,
                                    IntToDoubleFunction realizations,
                                    int size)
```
    Create a stochastic random variable.
    
    Parameters:
    
    time - the filtration time, set to 0.0 if not used.
    
    realizations - A map mapping integer (path or state) to double, representing this random variable.
    
    size - The size, i.e., number of paths.
- Method Detail
  - equals
```
public boolean equals(RandomVariable randomVariable)
```
    Description copied from interface: RandomVariable
    
    Compare this random variable with a given one
    
    Specified by:
    
    equals in interface RandomVariable
    
    Parameters:
    
    randomVariable - Random variable to compare with.
    
    Returns:
    
    True if this random variable and the given one are equal, otherwise false
  - getFiltrationTime
```
public double getFiltrationTime()
```
    Description copied from interface: RandomVariable
    
    Returns the filtration time.
    
    Specified by:
    
    getFiltrationTime in interface RandomVariable
    
    Returns:
    
    The filtration time.
  - getTypePriority
```
public int getTypePriority()
```
    Description copied from interface: RandomVariable
    
    Returns the type priority.
    
    Specified by:
    
    getTypePriority in interface RandomVariable
    
    Returns:
    
    The type priority.
    
    See Also:
    
    ssrn abstract 3246127
  - get
```
public double get(int pathOrState)
```
    Description copied from interface: RandomVariable
    
    Evaluate at a given path or state.
    
    Specified by:
    
    get in interface RandomVariable
    
    Parameters:
    
    pathOrState - Index of the path or state.
    
    Returns:
    
    Value of this random variable at the given path or state.
  - size
```
public int size()
```
    Description copied from interface: RandomVariable
    
    Returns the number of paths or states.
    
    Specified by:
    
    size in interface RandomVariable
    
    Returns:
    
    Number of paths or states.
  - getMin
```
public double getMin()
```
    Description copied from interface: RandomVariable
    
    Returns the minimum value attained by this random variable.
    
    Specified by:
    
    getMin in interface RandomVariable
    
    Returns:
    
    The minimum value.
  - getMax
```
public double getMax()
```
    Description copied from interface: RandomVariable
    
    Returns the maximum value attained by this random variable.
    
    Specified by:
    
    getMax in interface RandomVariable
    
    Returns:
    
    The maximum value.
  - getAverage
```
public double getAverage()
```
    Description copied from interface: RandomVariable
    
    Returns the expectation of this random variable. The result of this method has to agrees with average().doubleValue().
    
    Specified by:
    
    getAverage in interface RandomVariable
    
    Returns:
    
    The average assuming equi-distribution.
  - getAverage
```
public double getAverage(RandomVariable probabilities)
```
    Description copied from interface: RandomVariable
    
    Returns the expectation of this random variable for a given probability measure (weight). The result of this method is (mathematically) equivalent to
    this.mult(probabilities).getAverage() / probabilities.getAverage()
    while the internal implementation may differ, e.g. being more efficient by performing multiplication and summation in the same loop.
    
    Specified by:
    
    getAverage in interface RandomVariable
    
    Parameters:
    
    probabilities - The probability weights.
    
    Returns:
    
    The average assuming the given probability weights.
  - getVariance
```
public double getVariance()
```
    Description copied from interface: RandomVariable
    
    Returns the variance of this random variable, i.e., V where V = ((X-m)^2).getAverage() and X = this and m = X.getAverage().
    
    Specified by:
    
    getVariance in interface RandomVariable
    
    Returns:
    
    The average assuming equi-distribution.
  - getVariance
```
public double getVariance(RandomVariable probabilities)
```
    Description copied from interface: RandomVariable
    
    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).
    
    Specified by:
    
    getVariance in interface RandomVariable
    
    Parameters:
    
    probabilities - The probability weights.
    
    Returns:
    
    The average assuming the given probability weights.
  - getSampleVariance
```
public double getSampleVariance()
```
    Description copied from interface: RandomVariable
    
    Returns the sample variance of this random variable, i.e., V * size()/(size()-1) where V = getVariance().
    
    Specified by:
    
    getSampleVariance in interface RandomVariable
    
    Returns:
    
    The sample variance.
  - getStandardDeviation
```
public double getStandardDeviation()
```
    Description copied from interface: RandomVariable
    
    Returns the standard deviation of this random variable, i.e., sqrt(V) where V = ((X-m)^2).getAverage() and X = this and m = X.getAverage().
    
    Specified by:
    
    getStandardDeviation in interface RandomVariable
    
    Returns:
    
    The standard deviation assuming equi-distribution.
  - getStandardDeviation
```
public double getStandardDeviation(RandomVariable probabilities)
```
    Description copied from interface: RandomVariable
    
    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).
    
    Specified by:
    
    getStandardDeviation in interface RandomVariable
    
    Parameters:
    
    probabilities - The probability weights.
    
    Returns:
    
    The standard error assuming the given probability weights.
  - getStandardError
```
public double getStandardError()
```
    Description copied from interface: RandomVariable
    
    Returns the standard error (discretization error) of this random variable. For a Monte-Carlo simulation this is 1/Math.sqrt(n) * RandomVariable.getStandardDeviation().
    
    Specified by:
    
    getStandardError in interface RandomVariable
    
    Returns:
    
    The standard error assuming equi-distribution.
  - getStandardError
```
public double getStandardError(RandomVariable probabilities)
```
    Description copied from interface: RandomVariable
    
    Returns the standard error (discretization error) of this random variable. For a Monte-Carlo simulation this is 1/Math.sqrt(n) * RandomVariable.getStandardDeviation(RandomVariable).
    
    Specified by:
    
    getStandardError in interface RandomVariable
    
    Parameters:
    
    probabilities - The probability weights.
    
    Returns:
    
    The standard error assuming the given probability weights.
  - getQuantile
```
public double getQuantile(double quantile)
```
    Description copied from interface: RandomVariable
    
    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. The method will consider picewise constant values (with constant extrapolation) in the random variable. That is getQuantile(0) wiil return the smallest value and getQuantile(1) will return the largest value.
    
    Specified by:
    
    getQuantile in interface RandomVariable
    
    Parameters:
    
    quantile - The quantile level.
    
    Returns:
    
    The quantile value assuming equi-distribution.
  - getQuantile
```
public double getQuantile(double quantile,
                          RandomVariable probabilities)
```
    Description copied from interface: RandomVariable
    
    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.
    
    Specified by:
    
    getQuantile in interface RandomVariable
    
    Parameters:
    
    quantile - The quantile level.
    
    probabilities - The probability weights.
    
    Returns:
    
    The quantile value assuming the given probability weights.
  - getQuantileExpectation
```
public double getQuantileExpectation(double quantileStart,
                                     double quantileEnd)
```
    Description copied from interface: RandomVariable
    Returns the expectation over a quantile for this given random variable. The method will consider picewise constant values (with constant extrapolation) in the random variable. For a ≤ b the method returns (Σ_{a ≤ i ≤ b} x[i]) / (b-a+1), where
    
    a = min(max((n+1) * quantileStart - 1, 0, 1);
    
    b = min(max((n+1) * quantileEnd - 1, 0, 1);
    
    n = this.size();
    
    For quantileStart > quantileEnd the method returns getQuantileExpectation(quantileEnd, quantileStart).
    Specified by:
    
    getQuantileExpectation in interface RandomVariable
    
    Parameters:
    
    quantileStart - Lower bound of the integral.
    
    quantileEnd - Upper bound of the integral.
    
    Returns:
    
    The (conditional) expectation of the values between two quantile levels assuming equi-distribution.
  - getHistogram
```
public double[] getHistogram(double[] intervalPoints)
```
    Description copied from interface: RandomVariable
    Generates a Histogram based on the realizations stored in this random variable. The returned result array's length is intervalPoints.length+1.
    
    The value result[0] equals the relative frequency of values observed in the interval ( -infinity, intervalPoints[0] ].
    
    The value result[i] equals the relative frequency of values observed in the interval ( intervalPoints[i-1], intervalPoints[i] ].
    
    The value result[n] equals the relative frequency of values observed in the interval ( intervalPoints[n-1], infinity ).
    
    where n = intervalPoints.length. Note that the intervals are open on the left, closed on the right, i.e., result[i] contains the number of elements x with intervalPoints[i-1] < x ≤ intervalPoints[i]. Thus, is you have a random variable which only takes values contained in the (sorted) array possibleValues, then result = getHistogram(possibleValues) returns an array where result[i] is the relative frequency of occurrence of possibleValues[i]. The sum of result[i] over all i is equal to 1, except for uninitialized random variables where all values are 0.
    Specified by:
    
    getHistogram in interface RandomVariable
    
    Parameters:
    
    intervalPoints - Array of ascending values defining the interval boundaries.
    
    Returns:
    
    A histogram with respect to a provided interval.
  - getHistogram
```
public double[][] getHistogram(int numberOfPoints,
                               double standardDeviations)
```
    Description copied from interface: RandomVariable
    Generates a histogram based on the realizations stored in this random variable using interval points calculated from the arguments, see also RandomVariable.getHistogram(double[]). The interval points are set with equal distance over an the interval of the specified standard deviation. The interval points used are x[i] = mean + alpha[i] * standardDeviations * sigma where
    
    i = 0,..., numberOfPoints-1,
    
    alpha[i] = (i - (numberOfPoints-1)/2.0) / ((numberOfPoints-1)/2.0),
    
    mean = RandomVariable.getAverage(),
    
    sigma = RandomVariable.getStandardDeviation().
    
    The methods result is an array of two vectors, where result[0] are the intervals center points ('anchor points') and result[1] contains the relative frequency for the interval. The 'anchor point' for the interval (-infinity, x[0]) is x[0] - 1/2 (x[1]-x[0]) and the 'anchor point' for the interval (x[n], infinity) is x[n] + 1/2 (x[n]-x[n-1]). Here n = numberOfPoints is the number of interval points.
    Specified by:
    
    getHistogram in interface RandomVariable
    
    Parameters:
    
    numberOfPoints - The number of interval points.
    
    standardDeviations - The number of standard deviations defining the discretization radius.
    
    Returns:
    
    A histogram, given as double[2][], where result[0] are the center point of the intervals and result[1] is the value of RandomVariable.getHistogram(double[]) for the given the interval points. The length of result[0] and result[1] is numberOfPoints+1.
  - isDeterministic
```
public boolean isDeterministic()
```
    Description copied from interface: RandomVariable
    
    Check if this random variable is deterministic in the sense that it is represented by a single double value. Note that the methods returns false, if the random variable is represented by a vector where each element has the same value.
    
    Specified by:
    
    isDeterministic in interface RandomVariable
    
    Returns:
    
    True if this random variable is deterministic.
  - cache
```
public RandomVariable cache()
```
    Description copied from interface: RandomVariable
    
    Return a cacheable version of this object (often a self-reference). This method should be called when you store the object for later use, i.e., assign it, or when the object is consumed in a function, but later used also in another function.
    
    Specified by:
    
    cache in interface RandomVariable
    
    Returns:
    
    A cacheable version of this object (often a self-reference).
  - getRealizationsStream
```
public DoubleStream getRealizationsStream()
```
    Description copied from interface: RandomVariable
    
    Returns a stream of doubles corresponding to the realizations of this random variable.
    
    Specified by:
    
    getRealizationsStream in interface RandomVariable
    
    Returns:
    
    A stream of doubles corresponding to the realizations of this random variable.
  - getRealizations
```
public double[] getRealizations()
```
    Description copied from interface: RandomVariable
    
    Returns a vector representing the realization of this random variable. This method is merely useful for analysis. Its interpretation depends on the context (Monte-Carlo or lattice). The method does not expose an internal data model.
    
    Specified by:
    
    getRealizations in interface RandomVariable
    
    Returns:
    
    Vector of realizations of this random variable.
  - doubleValue
```
public Double doubleValue()
```
    Description copied from interface: RandomVariable
    
    Returns the double value if isDeterministic() is true. otherwise throws an UnsupportedOperationException.
    
    Specified by:
    
    doubleValue in interface RandomVariable
    
    Returns:
    
    The double value if isDeterministic() is true, otherwise throws an an UnsupportedOperationException.
  - getOperator
```
public IntToDoubleFunction getOperator()
```
    Description copied from interface: RandomVariable
    
    Returns the operator path → this.get(path) corresponding to this random variable.
    
    Specified by:
    
    getOperator in interface RandomVariable
    
    Returns:
    
    The operator path → this.get(path) corresponding to this random variable.
  - apply
```
public RandomVariable apply(DoubleUnaryOperator operator)
```
    Description copied from interface: RandomVariable
    
    Applies x → operator(x) to this random variable. It returns a new random variable with the result.
    
    Specified by:
    
    apply in interface RandomVariable
    
    Parameters:
    
    operator - An unary operator/function, mapping double to double.
    
    Returns:
    
    New random variable with the result of the function.
  - apply
```
public RandomVariable apply(DoubleBinaryOperator operator,
                            RandomVariable argument)
```
    Description copied from interface: RandomVariable
    
    Applies x → operator(x,y) to this random variable, where x is this random variable and y is a given random variable. It returns a new random variable with the result.
    
    Specified by:
    
    apply in interface RandomVariable
    
    Parameters:
    
    operator - A binary operator/function, mapping (double,double) to double.
    
    argument - A random variable.
    
    Returns:
    
    New random variable with the result of the function.
  - apply
```
public RandomVariable apply(DoubleTernaryOperator operator,
                            RandomVariable argument1,
                            RandomVariable argument2)
```
    Description copied from interface: RandomVariable
    
    Applies x → operator(x,y,z) to this random variable, where x is this random variable and y and z are given random variable. It returns a new random variable with the result.
    
    Specified by:
    
    apply in interface RandomVariable
    
    Parameters:
    
    operator - A ternary operator/function, mapping (double,double,double) to double.
    
    argument1 - A random variable representing y.
    
    argument2 - A random variable representing z.
    
    Returns:
    
    New random variable with the result of the function.
  - cap
```
public RandomVariable cap(double cap)
```
    Description copied from interface: RandomVariable
    
    Applies x → min(x,cap) to this random variable. It returns a new random variable with the result.
    
    Specified by:
    
    cap in interface RandomVariable
    
    Parameters:
    
    cap - The cap.
    
    Returns:
    
    New random variable with the result of the function.
  - floor
```
public RandomVariable floor(double floor)
```
    Description copied from interface: RandomVariable
    
    Applies x → max(x,floor) to this random variable. It returns a new random variable with the result.
    
    Specified by:
    
    floor in interface RandomVariable
    
    Parameters:
    
    floor - The floor.
    
    Returns:
    
    New random variable with the result of the function.
  - add
```
public RandomVariable add(double value)
```
    Description copied from interface: RandomVariable
    
    Applies x → x + value to this random variable. It returns a new random variable with the result.
    
    Specified by:
    
    add in interface RandomVariable
    
    Parameters:
    
    value - The value to add.
    
    Returns:
    
    New random variable with the result of the function.
  - sub
```
public RandomVariable sub(double value)
```
    Description copied from interface: RandomVariable
    
    Applies x → x - value to this random variable.
    
    Specified by:
    
    sub in interface RandomVariable
    
    Parameters:
    
    value - The value to subtract.
    
    Returns:
    
    New random variable with the result of the function.
  - mult
```
public RandomVariable mult(double value)
```
    Description copied from interface: RandomVariable
    
    Applies x → x * value to this random variable.
    
    Specified by:
    
    mult in interface RandomVariable
    
    Parameters:
    
    value - The value to multiply.
    
    Returns:
    
    New random variable with the result of the function.
  - div
```
public RandomVariable div(double value)
```
    Description copied from interface: RandomVariable
    
    Applies x → x / value to this random variable.
    
    Specified by:
    
    div in interface RandomVariable
    
    Parameters:
    
    value - The value to divide.
    
    Returns:
    
    New random variable with the result of the function.
  - pow
```
public RandomVariable pow(double exponent)
```
    Description copied from interface: RandomVariable
    
    Applies x → pow(x,exponent) to this random variable.
    
    Specified by:
    
    pow in interface RandomVariable
    
    Parameters:
    
    exponent - The exponent.
    
    Returns:
    
    New random variable with the result of the function.
  - average
```
public RandomVariable average()
```
    Description copied from interface: RandomVariable
    
    Returns a random variable which is deterministic and corresponds the expectation of this random variable.
    
    Specified by:
    
    average in interface RandomVariable
    
    Returns:
    
    New random variable being the expectation of this random variable.
  - getConditionalExpectation
```
public RandomVariable getConditionalExpectation(ConditionalExpectationEstimator conditionalExpectationOperator)
```
    Description copied from interface: RandomVariable
    
    Returns the conditional expectation using a given conditional expectation estimator.
    
    Specified by:
    
    getConditionalExpectation in interface RandomVariable
    
    Parameters:
    
    conditionalExpectationOperator - A given conditional expectation estimator.
    
    Returns:
    
    The conditional expectation of this random variable (as a random variable)
  - squared
```
public RandomVariable squared()
```
    Description copied from interface: RandomVariable
    
    Applies x → x * x to this random variable.
    
    Specified by:
    
    squared in interface RandomVariable
    
    Returns:
    
    New random variable with the result of the function.
  - sqrt
```
public RandomVariable sqrt()
```
    Description copied from interface: RandomVariable
    
    Applies x → sqrt(x) to this random variable.
    
    Specified by:
    
    sqrt in interface RandomVariable
    
    Returns:
    
    New random variable with the result of the function.
  - exp
```
public RandomVariableFromFloatArray exp()
```
    Description copied from interface: RandomVariable
    
    Applies x → exp(x) to this random variable.
    
    Specified by:
    
    exp in interface RandomVariable
    
    Returns:
    
    New random variable with the result of the function.
  - log
```
public RandomVariableFromFloatArray log()
```
    Description copied from interface: RandomVariable
    
    Applies x → log(x) to this random variable.
    
    Specified by:
    
    log in interface RandomVariable
    
    Returns:
    
    New random variable with the result of the function.
  - sin
```
public RandomVariable sin()
```
    Description copied from interface: RandomVariable
    
    Applies x → sin(x) to this random variable.
    
    Specified by:
    
    sin in interface RandomVariable
    
    Returns:
    
    New random variable with the result of the function.
  - cos
```
public RandomVariable cos()
```
    Description copied from interface: RandomVariable
    
    Applies x → cos(x) to this random variable.
    
    Specified by:
    
    cos in interface RandomVariable
    
    Returns:
    
    New random variable with the result of the function.
  - add
```
public RandomVariable add(RandomVariable randomVariable)
```
    Description copied from interface: RandomVariable
    
    Applies x → x+randomVariable to this random variable.
    
    Specified by:
    
    add in interface RandomVariable
    
    Parameters:
    
    randomVariable - A random variable (compatible with this random variable).
    
    Returns:
    
    New random variable with the result of the function.
  - sub
```
public RandomVariable sub(RandomVariable randomVariable)
```
    Description copied from interface: RandomVariable
    
    Applies x → x-randomVariable to this random variable.
    
    Specified by:
    
    sub in interface RandomVariable
    
    Parameters:
    
    randomVariable - A random variable (compatible with this random variable).
    
    Returns:
    
    New random variable with the result of the function.
  - bus
```
public RandomVariable bus(RandomVariable randomVariable)
```
    Description copied from interface: RandomVariable
    
    Applies x → randomVariable-x to this random variable.
    
    Specified by:
    
    bus in interface RandomVariable
    
    Parameters:
    
    randomVariable - A random variable (compatible with this random variable).
    
    Returns:
    
    New random variable with the result of the function.
  - mult
```
public RandomVariable mult(RandomVariable randomVariable)
```
    Description copied from interface: RandomVariable
    
    Applies x → x*randomVariable to this random variable.
    
    Specified by:
    
    mult in interface RandomVariable
    
    Parameters:
    
    randomVariable - A random variable (compatible with this random variable).
    
    Returns:
    
    New random variable with the result of the function.
  - div
```
public RandomVariable div(RandomVariable randomVariable)
```
    Description copied from interface: RandomVariable
    
    Applies x → x/randomVariable to this random variable.
    
    Specified by:
    
    div in interface RandomVariable
    
    Parameters:
    
    randomVariable - A random variable (compatible with this random variable).
    
    Returns:
    
    New random variable with the result of the function.
  - vid
```
public RandomVariable vid(RandomVariable randomVariable)
```
    Description copied from interface: RandomVariable
    
    Applies x → randomVariable/x to this random variable.
    
    Specified by:
    
    vid in interface RandomVariable
    
    Parameters:
    
    randomVariable - A random variable (compatible with this random variable).
    
    Returns:
    
    New random variable with the result of the function.
  - cap
```
public RandomVariable cap(RandomVariable randomVariable)
```
    Description copied from interface: RandomVariable
    
    Applies x → min(x,cap) to this random variable.
    
    Specified by:
    
    cap in interface RandomVariable
    
    Parameters:
    
    randomVariable - The cap. A random variable (compatible with this random variable).
    
    Returns:
    
    New random variable with the result of the function.
  - floor
```
public RandomVariable floor(RandomVariable randomVariable)
```
    Description copied from interface: RandomVariable
    
    Applies x → max(x,floor) to this random variable.
    
    Specified by:
    
    floor in interface RandomVariable
    
    Parameters:
    
    randomVariable - The floor. A random variable (compatible with this random variable).
    
    Returns:
    
    New random variable with the result of the function.
  - accrue
```
public RandomVariable accrue(RandomVariable rate,
                             double periodLength)
```
    Description copied from interface: RandomVariable
    
    Applies x → x * (1.0 + rate * periodLength) to this random variable.
    
    Specified by:
    
    accrue in interface RandomVariable
    
    Parameters:
    
    rate - The accruing rate. A random variable (compatible with this random variable).
    
    periodLength - The period length
    
    Returns:
    
    New random variable with the result of the function.
  - discount
```
public RandomVariable discount(RandomVariable rate,
                               double periodLength)
```
    Description copied from interface: RandomVariable
    
    Applies x → x / (1.0 + rate * periodLength) to this random variable.
    
    Specified by:
    
    discount in interface RandomVariable
    
    Parameters:
    
    rate - The discounting rate. A random variable (compatible with this random variable).
    
    periodLength - The period length
    
    Returns:
    
    New random variable with the result of the function.
  - choose
```
public RandomVariable choose(RandomVariable valueIfTriggerNonNegative,
                             RandomVariable valueIfTriggerNegative)
```
    Description copied from interface: RandomVariable
    
    Applies x → (x ≥ 0 ? valueIfTriggerNonNegative : valueIfTriggerNegative)
    
    Specified by:
    
    choose in interface RandomVariable
    
    Parameters:
    
    valueIfTriggerNonNegative - The value used if this is greater or equal 0
    
    valueIfTriggerNegative - The value used if the this is less than 0
    
    Returns:
    
    New random variable with the result of the function.
  - invert
```
public RandomVariable invert()
```
    Description copied from interface: RandomVariable
    
    Applies x → 1/x to this random variable.
    
    Specified by:
    
    invert in interface RandomVariable
    
    Returns:
    
    New random variable with the result of the function.
  - abs
```
public RandomVariable abs()
```
    Description copied from interface: RandomVariable
    
    Applies x → Math.abs(x), i.e. x → |x| to this random variable.
    
    Specified by:
    
    abs in interface RandomVariable
    
    Returns:
    
    New random variable with the result of the function.
  - addProduct
```
public RandomVariable addProduct(RandomVariable factor1,
                                 double factor2)
```
    Description copied from interface: RandomVariable
    
    Applies x → x + factor1 * factor2
    
    Specified by:
    
    addProduct in interface RandomVariable
    
    Parameters:
    
    factor1 - The factor 1. A random variable (compatible with this random variable).
    
    factor2 - The factor 2.
    
    Returns:
    
    New random variable with the result of the function.
  - addProduct
```
public RandomVariable addProduct(RandomVariable factor1,
                                 RandomVariable factor2)
```
    Description copied from interface: RandomVariable
    
    Applies x → x + factor1 * factor2
    
    Specified by:
    
    addProduct in interface RandomVariable
    
    Parameters:
    
    factor1 - The factor 1. A random variable (compatible with this random variable).
    
    factor2 - The factor 2. A random variable (compatible with this random variable).
    
    Returns:
    
    New random variable with the result of the function.
  - addSumProduct
```
public RandomVariable addSumProduct(List<RandomVariable> factor1,
                                    List<RandomVariable> factor2)
```
    Description copied from interface: RandomVariable
    
    Applies \( x \mapsto x + \sum_{i=0}^{n-1} factor1_{i} * factor2_{i}
    
    Specified by:
    
    addSumProduct in interface RandomVariable
    
    Parameters:
    
    factor1 - The factor 1. A list of random variables (compatible with this random variable).
    
    factor2 - The factor 2. A list of random variables (compatible with this random variable).
    
    Returns:
    
    New random variable with the result of the function.
  - addRatio
```
public RandomVariable addRatio(RandomVariable numerator,
                               RandomVariable denominator)
```
    Description copied from interface: RandomVariable
    
    Applies x → x + numerator / denominator
    
    Specified by:
    
    addRatio in interface RandomVariable
    
    Parameters:
    
    numerator - The numerator of the ratio to add. A random variable (compatible with this random variable).
    
    denominator - The denominator of the ratio to add. A random variable (compatible with this random variable).
    
    Returns:
    
    New random variable with the result of the function.
  - subRatio
```
public RandomVariable subRatio(RandomVariable numerator,
                               RandomVariable denominator)
```
    Description copied from interface: RandomVariable
    
    Applies x → x - numerator / denominator
    
    Specified by:
    
    subRatio in interface RandomVariable
    
    Parameters:
    
    numerator - The numerator of the ratio to sub. A random variable (compatible with this random variable).
    
    denominator - The denominator of the ratio to sub. A random variable (compatible with this random variable).
    
    Returns:
    
    New random variable with the result of the function.
  - isNaN
```
public RandomVariable isNaN()
```
    Description copied from interface: RandomVariable
    
    Applies x → (Double.isNaN(x) ? 1.0 : 0.0)
    
    Specified by:
    
    isNaN in interface RandomVariable
    
    Returns:
    
    A random variable which is 1.0 for all states that are NaN, otherwise 0.0.
  - toString
```
public String toString()
```
    Overrides:
    
    toString in class Object

Class RandomVariableFromFloatArray

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Methods inherited from interface net.finmath.stochastic.RandomVariable

Constructor Detail

RandomVariableFromFloatArray

RandomVariableFromFloatArray

RandomVariableFromFloatArray

RandomVariableFromFloatArray

RandomVariableFromFloatArray

RandomVariableFromFloatArray

RandomVariableFromFloatArray

RandomVariableFromFloatArray

RandomVariableFromFloatArray

RandomVariableFromFloatArray

RandomVariableFromFloatArray

Method Detail

equals

getFiltrationTime

getTypePriority

get

size

getMin

getMax

getAverage

getAverage

getVariance

getVariance

getSampleVariance

getStandardDeviation

getStandardDeviation

getStandardError

getStandardError

getQuantile

getQuantile

getQuantileExpectation

getHistogram

getHistogram

isDeterministic

cache

getRealizationsStream

getRealizations

doubleValue

getOperator

apply

apply

apply

cap

floor

add

sub

mult

div

pow

average

getConditionalExpectation

squared

sqrt

exp

log

sin

cos

add

sub

bus

mult

div

vid

cap

floor

accrue

discount

choose

invert

abs

addProduct

addProduct

addSumProduct

addRatio