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)
- Version0.6.2
- R version≥ 2.0.0
- LicenseGPL (≥ 3)
- Needs compilation?No
- Last release03/10/2022
Documentation
- VignetteDecaying-Dimerization Reaction Set (Gillespie, 2001)
- VignetteSIRS metapopulation model (Pineda-Krch, 2008)
- VignetteLinear Chain System (Cao et al., 2004)
- VignettePearl-Verhulst Logistic growth model (Kot, 2001)
- VignetteLotka predator-prey model (Gillespie, 1977; Kot, 2001)
- VignetteRadioactive decay model (Gillespie, 1977)
- VignetteRosenzweig-MacArthur predator-prey model (Pineda-Krch et al., 2007)
- VignetteKermack-McKendrick SIR model (Brown & Rothery, 1993)
- MaterialREADME
- MaterialNEWS
- In ViewsDifferentialEquations
Team
Robrecht Cannoodt
Mario Pineda-Krch
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- Depends1 package
- Imports4 packages
- Suggests3 packages
- Reverse Imports1 package
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