GillespieSSA: Gillespie's Stochastic Simulation Algorithm (SSA)
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.
Pineda-Krch et al. (2008) <doi:10.18637/jss.v025.i12>.
Documentation:
| Reference manual: |
GillespieSSA.pdf |
| Vignettes: |
Decaying-Dimerization Reaction Set (Gillespie, 2001) (source, R code)
SIRS metapopulation model (Pineda-Krch, 2008) (source, R code)
Linear Chain System (Cao et al., 2004) (source, R code)
Pearl-Verhulst Logistic growth model (Kot, 2001) (source, R code)
Lotka predator-prey model (Gillespie, 1977; Kot, 2001) (source, R code)
Radioactive decay model (Gillespie, 1977) (source, R code)
Rosenzweig-MacArthur predator-prey model (Pineda-Krch et al., 2007) (source, R code)
Kermack-McKendrick SIR model (Brown & Rothery, 1993) (source, R code)
|
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Reverse dependencies:
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