stochastic_rk


stochastic_rk, a Fortran77 code which implements Runge-Kutta integration methods for stochastic differential equations.

Licensing:

The computer code and data files described and made available on this web page are distributed under the MIT license

Languages:

stochastic_rk is available in a C version and a C++ version and a Fortran77 version and a Fortran90 version and a MATLAB version.

Related Data and Programs:

stochastic_rk_test

black_scholes, a Fortran77 library which implements some simple approaches to the Black-Scholes option valuation theory;

COLORED_NOISE, a Fortran77 library which generates samples of noise obeying a 1/f^alpha power law.

FEYNMAN_KAC_2D, a Fortran77 program which demonstrates the use of the Feynman-Kac algorithm for solving a certain 2D partial differential equation.

ORNSTEIN_UHLENBECK, a Fortran77 library which approximates solutions of the Ornstein-Uhlenbeck stochastic differential equation (SDE) using the Euler method and the Euler-Maruyama method.

PCE_ODE_HERMITE, a Fortran77 program which sets up a simple scalar ODE for exponential decay with an uncertain decay rate, using a polynomial chaos expansion in terms of Hermite polynomials.

PINK_NOISE, a Fortran77 library which computes a "pink noise" signal obeying a 1/f power law.

SDE, a Fortran77 library which illustrates the properties of stochastic differential equations (SDE's), and common algorithms for their analysis, by Desmond Higham;

STOCHASTIC_DIFFUSION, Fortran77 functions which implement several versions of a stochastic diffusivity coefficient.

Reference:

  1. Jeremy Kasdin,
    Runge-Kutta algorithm for the numerical integration of stochastic differential equations,
    Journal of Guidance, Control, and Dynamics,
    Volume 18, Number 1, January-February 1995, pages 114-120.
  2. Jeremy Kasdin,
    Discrete Simulation of Colored Noise and Stochastic Processes and 1/f^a Power Law Noise Generation,
    Proceedings of the IEEE,
    Volume 83, Number 5, 1995, pages 802-827.

Source Code:


Last revised on 16 December 2023.