# expectation (3) - Linux Man Pages

## NAME

QuantLib::G2Process - G2 stochastic process

## SYNOPSIS

#include <ql/processes/g2process.hpp>

Inherits QuantLib::StochasticProcess.

### Public Member Functions

G2Process (Real a, Real sigma, Real b, Real eta, Real rho)

Real x0 () const

Real y0 () const

Real a () const

Real sigma () const

Real b () const

Real eta () const

Real rho () const

StochasticProcess interface

Size size () const
returns the number of dimensions of the stochastic process
Disposable< Array > initialValues () const
returns the initial values of the state variables
Disposable< Array > drift (Time t, const Array &x) const
returns the drift part of the equation, i.e., \$ mu(t, mathrm{x}_t) \$
Disposable< Matrix > diffusion (Time t, const Array &x) const
returns the diffusion part of the equation, i.e. \$ igma(t, mathrm{x}_t) \$
Disposable< Array > expectation (Time t0, const Array &x0, Time dt) const

Disposable< Matrix > stdDeviation (Time t0, const Array &x0, Time dt) const

Disposable< Matrix > covariance (Time t0, const Array &x0, Time dt) const

## Detailed Description

G2 stochastic process

## Member Function Documentation

### Disposable<Array> expectation (Time t0, const Array & x0, Time dt) const [virtual]

returns the expectation \$ E(mathrm{x}_{t_0 + Delta t} | mathrm{x}_{t_0} = mathrm{x}_0) \$ of the process after a time interval \$ Delta t \$ according to the given discretization. This method can be overridden in derived classes which want to hard-code a particular discretization.

Reimplemented from StochasticProcess.

### Disposable<Matrix> stdDeviation (Time t0, const Array & x0, Time dt) const [virtual]

returns the standard deviation \$ S(mathrm{x}_{t_0 + Delta t} | mathrm{x}_{t_0} = mathrm{x}_0) \$ of the process after a time interval \$ Delta t \$ according to the given discretization. This method can be overridden in derived classes which want to hard-code a particular discretization.

Reimplemented from StochasticProcess.

### Disposable<Matrix> covariance (Time t0, const Array & x0, Time dt) const [virtual]

returns the covariance \$ V(mathrm{x}_{t_0 + Delta t} | mathrm{x}_{t_0} = mathrm{x}_0) \$ of the process after a time interval \$ Delta t \$ according to the given discretization. This method can be overridden in derived classes which want to hard-code a particular discretization.

Reimplemented from StochasticProcess.

## Author

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