com.numericalmethod.suanshu.stats.stochasticprocess.multivariate.sde.coefficients

Interface Diffusion

All Superinterfaces:

java.io.Serializable

All Known Implementing Classes:

ConstantSigma1, ConstantSigma2, Sigma

public interface Diffusion
extends java.io.Serializable

This represents the diffusion term, σ, of an SDE. It is of this form: σ(dt, Xt, Zt, ...).

Note that we are passing in the time differential, dt, instead of the time itself. If we want to compute for a time t, the subclass would need to accumulate the dts explicitly.

See Also:

"Fima C. Klebaner. Introduction to Stochastic Calculus with Applications. 2nd ed. Section 4.7. Imperial College Press. 2006."

Method Summary

Modifier and Type	Method and Description
Matrix	evaluate(Ft ft) σ(dt, Xt, Zt, ...)
int	nCols() Get the number of independent Brownian motions.
int	nRows() Get the dimension of the process.

Method Detail

evaluate

Matrix evaluate(Ft ft)

σ(dt, Xt, Zt, ...)

Parameters:

ft - filtration

Returns:

a diffusion matrix

nRows

int nRows()

Get the dimension of the process.

Returns:

the number of rows in the diffusion matrix

nCols

int nCols()

Get the number of independent Brownian motions.

Returns:

the number of columns in the diffusion matrix