- QuantLib
- G2Process
G2 stochastic process More...
#include <ql/processes/g2process.hpp>

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 |
G2 stochastic process
| 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.