SimBIID-package: Simulation-based inference for infectious disease models
In SimBIID: Simulation-Based Inference Methods for Infectious Disease Models
Description
Package implements various simulation-based inference routines for infectious
disease models.
Details
Provides some code to run simulations of state-space models, and then
use these in the Approximate Bayesian Computation Sequential Monte Carlo (ABC-SMC)
algorithm of Toni et al. (2009) <doi:10.1098/rsif.2008.0172> and a bootstrap particle
filter based particle Markov chain Monte Carlo (PMCMC) algorithm
(Andrieu et al., 2010 <doi:10.1111/j.1467-9868.2009.00736.x>).
Also provides functions to plot and summarise the outputs.
Author(s)
Trevelyan J. McKinley <t.mckinley@exeter.ac.uk>
SimBIID documentation built on Feb. 4, 2021, 9:07 a.m.
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Description
Package implements various simulation-based inference routines for infectious disease models.
Details
Provides some code to run simulations of state-space models, and then use these in the Approximate Bayesian Computation Sequential Monte Carlo (ABC-SMC) algorithm of Toni et al. (2009) <doi:10.1098/rsif.2008.0172> and a bootstrap particle filter based particle Markov chain Monte Carlo (PMCMC) algorithm (Andrieu et al., 2010 <doi:10.1111/j.1467-9868.2009.00736.x>). Also provides functions to plot and summarise the outputs.
Author(s)
Trevelyan J. McKinley <t.mckinley@exeter.ac.uk>
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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