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cff-version: 1.2.0
message: 'To cite package "StochSimR" in publications use:'
type: software
license: MIT
title: 'StochSimR: Stochastic Process Simulation Engine'
version: 1.0.0
doi: 10.32614/CRAN.package.StochSimR
abstract: A modular simulation engine for stochastic processes. Provides exact and
  approximate simulation methods for Poisson processes, Brownian motion, discrete-time
  Markov chains, Levy processes (gamma, normal inverse Gaussian, variance-gamma, alpha-stable),
  Merton jump-diffusion models, Hawkes self-exciting processes, geometric Brownian
  motion, and Ornstein-Uhlenbeck mean-reverting diffusions. Includes variance reduction
  techniques (antithetic variates, control variates, importance sampling, stratified
  sampling), parallel simulation via the 'future' framework, rare-event simulation
  (cross-entropy and multilevel splitting), path visualization, and summary statistics.
  Methods are based on Glasserman (2003) <https://doi.org/10.1007/978-0-387-21617-1>
  and Asmussen & Glynn (2007) <https://doi.org/10.1007/978-0-387-69033-9>.
authors:
- family-names: Kundu
  given-names: Ayush
  email: ayushkundu25@iitk.ac.in
  orcid: https://orcid.org/0009-0009-8715-2624
repository: https://ayush291202.r-universe.dev
repository-code: https://github.com/Ayush291202/StochSimR
commit: 5f4602a5f9852d5afd16ba82d1dca916de19a93e
url: https://github.com/Ayush291202/StochSimR
date-released: '2026-04-01'
contact:
- family-names: Kundu
  given-names: Ayush
  email: ayushkundu25@iitk.ac.in
  orcid: https://orcid.org/0009-0009-8715-2624