StochSimR: Stochastic Process Simulation Engine
A modular simulation engine for a wide range of stochastic
processes. Provides exact and approximate simulation methods for Poisson
processes (homogeneous and inhomogeneous), Brownian motion (standard,
drifted, and bridge), discrete- and continuous-time Markov chains,
birth-death processes, the Yule pure-birth process, infinitesimal
generator matrix utilities, Markovian queuing systems (M/M/1, M/M/c,
M/M/c/K) with exact steady-state statistics, 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 visualisation, and summary statistics. Methods are based
on Glasserman (2003) <doi:10.1007/978-0-387-21617-1>, Asmussen & Glynn
(2007) <doi:10.1007/978-0-387-69033-9>, Norris (1997)
<doi:10.1017/CBO9780511810633>, and Kleinrock (1975, ISBN:0471491101).
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