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

Class Expectation

java.lang.Object

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

All Implemented Interfaces:

java.io.Serializable

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

This class computes the expectation of the following class of integrals.

    /
 E( | f(B(t)) dt )
    /
 

f is not necessarily an adapted function.

The Brownian paths are generated by Monte Carlo simulations.

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
Integrator	I the integrator to compute the integral for each filtration/path
int	n the number of discretization in the integral time interval
int	nSim the number of simulations
double	t0 the beginning time of the integral time interval
double	t1 the ending time of the integral time interval

Constructor Summary

Constructors

Constructor and Description
Expectation(Integrator I, double t0, double t1, int n, int nSim) Compute the expectation for the integral of a stochastic process.

Method Summary

Modifier and Type	Method and Description
double	mean() Compute the mean of the integral.
double	var() Compute the variance of the integral.

Methods inherited from class java.lang.Object

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

Field Detail

I

public final Integrator I

the integrator to compute the integral for each filtration/path

t0

public final double t0

the beginning time of the integral time interval

t1

public final double t1

the ending time of the integral time interval

n

public final int n

the number of discretization in the integral time interval

nSim

public final int nSim

the number of simulations

Constructor Detail

Expectation

public Expectation(Integrator I,
                   double t0,
                   double t1,
                   int n,
                   int nSim)

Compute the expectation for the integral of a stochastic process.

Parameters:

I - the integral of a stochastic process

t0 - the beginning time of the integral time interval

t1 - the ending time of the integral time interval

n - the number of discretization in the integral time interval

nSim - the number of simulations

Method Detail

mean

public double mean()

Compute the mean of the integral.

Returns:

the mean of the integral

var

public double var()

Compute the variance of the integral.

Returns:

the variance of the integral