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 |
| 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 depends: | Sim.DiffProcGUI |