G2Process Class Reference
[Stochastic processes]
#include <ql/processes/g2process.hpp>
Inheritance diagram for G2Process:

Detailed Description
G2 stochastic process
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., ![]() | |
Disposable< Matrix > | diffusion (Time t, const Array &x) const |
returns the diffusion part of the equation, i.e. ![]() | |
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 |
Member Function Documentation
Disposable<Array> expectation | ( | Time | t0, | |
const Array & | x0, | |||
Time | dt | |||
) | const [virtual] |
returns the expectation of the process after a time interval
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 of the process after a time interval
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 of the process after a time interval
according to the given discretization. This method can be overridden in derived classes which want to hard-code a particular discretization.
Reimplemented from StochasticProcess.