Packaged: Tue Jan 15 06:35:27 2008; pineda

Packaged: Thu Jan 17 07:33:11 2008; pineda

Packaged: Fri Feb  1 02:15:39 2008; pineda

Description: GillespieSSA provides a simple to use, intuitive, and
extensible interface to several stochastic simulation
algorithms for generating simulated trajectories of finite
population continuous-time model. Currently it implements
Gillespie's exact stochastic simulation algorithm (Direct
method) and several approximate methods (Explicit tau-leap,
Binomial tau-leap, and Optimized tau-leap). The package also
contains a library of template models that can be run as demo
models and can easily be customized and extended. Currently the
following models are included, decaying-dimerization reaction
set, linear chain system, logistic growth model, Lotka
predator-prey model, Rosenzweig-MacArthur predator-prey model,
Kermack-McKendrick SIR model, and a metapopulation SIRS model.
X-CRAN-Comment: Orphaned on 2014-01-12 as maintainer address

Description: Provides a simple to use, intuitive, and
following models are included, 'Decaying-Dimerization' reaction
set, linear chain system, logistic growth model, 'Lotka'
'Kermack-McKendrick' SIR model, and a 'metapopulation' SIRS model.
person("Mario", "Pineda-Krch", role = c("aut")),
Robrecht Cannoodt [aut, cre] (<https://orcid.org/0000-0003-3641-729X>)

Imports: grDevices, graphics, methods, stats, utils

Title: Gillespie's Stochastic Simulation Algorithm for Impatient People
Description: A fast, scalable, and versatile framework for
simulating large systems with Gillespie's Stochastic Simulation
Algorithm ('SSA').  This package is the spiritual successor to the
'GillespieSSA' package originally written by Mario Pineda-Krch.
Benefits of this package include major speed improvements (>100x),
easier to understand documentation, and many unit tests that try to
ensure the package works as intended. Cannoodt and Saelens et al. (2020)
Imports: assertthat, dplyr, dynutils, Matrix, methods, purrr, Rcpp (>=
0.12.3), RcppXPtrUtils, readr, rlang, stringr, tidyr
Suggests: covr, ggplot2, GillespieSSA, knitr, rmarkdown, testthat (>=
Author: Robrecht Cannoodt [aut, cre] (<https://orcid.org/0000-0003-3641-729X>),