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VectorBrownianMotion Class Reference

#include <StochasticProcesses.h>

Inheritance diagram for VectorBrownianMotion:

List of all members.

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Detailed Description

Brownian motion in any dimension.

Definition at line 77 of file StochasticProcesses.h.

Public Member Functions
	VectorBrownianMotion (int dim, int T, Real dt)
	VectorBrownianMotion (int dim, int T, Real dt, RealVector &x0)
void	timeStep (int t)
Static Public Member Functions
void	testPathFunctional (int t, int T, int nPath)

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Constructor & Destructor Documentation

VectorBrownianMotion::VectorBrownianMotion (  int    dim, int    T, Real    dt )

Brownian motion starts at zero. Parameters: dim  dimension. T  number of time steps to horizon. dt  size of time step.

VectorBrownianMotion::VectorBrownianMotion (  int    dim, int    T, Real    dt, RealVector &    x0 )

Parameters: dim  dimension. T  number of time steps to horizon. dt  size of time step. x  starting point of Brownian motion.

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Member Function Documentation

void VectorBrownianMotion::timeStep (  int    t )  [virtual]

Time step t->t+1 based on current Z-increments. Implements StochasticProcess< RealVector, Real >.

void VectorBrownianMotion::testPathFunctional (  int    t, int    T, int    nPath )  [static]

Allocates a two dimensional Brownian motion X with T time steps of size dt=0.01 to the horizon. The path functional f is defined to be f=X_1(T)+X_2(T). A path of X is computed to time t and the functional conditioned on the state at time t. The conditional distribution is normal with mean X_1(t)+X_2(t) and variance 2*(T-t)*dt. The conditional mean and variance are computed from a sample of size nPath and compared with the analytic values.

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The documentation for this class was generated from the following file:

• StochasticProcesses.h

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