com.numericalmethod.suanshu.stats.stochasticprocess.univariate.integration.sde

Class Expectation

java.lang.Object

com.numericalmethod.suanshu.stats.stochasticprocess.univariate.integration.sde.Expectation

All Implemented Interfaces:

java.io.Serializable

public class Expectation
extends java.lang.Object
implements java.io.Serializable

This class computes the expectation of a stochastic integral. It does so by Monte Carlo simulation over a discretized interval, compute the mean (the expectation) and the variance.

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
double	value the value of the integral
double	variance the variance of the integral

Constructor Summary

Constructors

Constructor and Description
Expectation(Construction integrand, double x0, int N) Compute an expectation of a stochastic integral.
Expectation(SDE integrand, double T0, double T, int nT, double x0, int N) Compute an expectation of a stochastic integral.

Method Summary

Modifier and Type	Method and Description
double	value() Get the integral value.
double	variance() Get the integral variance.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

value

public final double value

the value of the integral

variance

public final double variance

the variance of the integral

Constructor Detail

Expectation

public Expectation(Construction integrand,
                   double x0,
                   int N)

Compute an expectation of a stochastic integral.

Parameters:

integrand - a simulation of the integrand

x0 - the initial value

N - the number of simulations

Expectation

public Expectation(SDE integrand,
                   double T0,
                   double T,
                   int nT,
                   double x0,
                   int N)

Compute an expectation of a stochastic integral.

Parameters:

integrand - the integrand SDE

T0 - the beginning of the integral time interval

T - the ending of the integral time interval

nT - the number of sub-intervals in [T0, T], hence time interval discretization

x0 - the initial value

N - the number of simulations

Method Detail

value

public double value()

Get the integral value.

Returns:

the integral value

variance

public double variance()

Get the integral variance.

Returns:

the integral variance