Sim.DiffProc: Simulation of Diffusion Processes

Simulation of diffusion processes and numerical solution of stochastic differential equations. Analysis of discrete-time approximations for stochastic differential equations (SDE) driven by Wiener processes,in financial and actuarial modeling and other areas of application for example modelling and simulation of dispersion in shallow water using the attractive center (K.BOUKHETALA, 1996). Approximated the evolution of conditional law a diffusion process with three methods Euler, Kessler and Shoji-Ozaki. Simulation and statistical analysis of the first passage time (FPT) and M-samples of the random variable X(v) given by a simulated diffusion process.

Version: 2.2
Depends: R (≥ 2.12.0), tcltk, tcltk2, stats4, rgl (≥ 0.92.798) , xlsx (≥ 0.4.0)
Published: 2012-02-13
Author: BOUKHETALA Kamal, GUIDOUM Arsalane
Maintainer: BOUKHETALA Kamal <kboukhetala at usthb.dz>
License: GPL (≥ 2)
URL: http://www.r-project.org , http://www.inside-r.org/packages/cran/Sim.DiffProc
Classification/ACM: F.0, G.3
Citation: Sim.DiffProc citation info
In views: DifferentialEquations
CRAN checks: Sim.DiffProc results

Downloads:

Package source: Sim.DiffProc_2.2.tar.gz
MacOS X binary: not available, see check log.
Windows binary: Sim.DiffProc_2.2.zip
Reference manual: Sim.DiffProc.pdf
News/ChangeLog:NEWS
Old sources: Sim.DiffProc archive

Reverse dependencies:

Reverse depends: Sim.DiffProcGUI