bayessir-package: PMMH algorithm for time-varying SIRS model
In vnminin/bayessir: Particle marginal Metropolis-Hastings (PMMH) algorithm for time-varying Susceptible-Infectious-Recovered-Susceptible (SIRS) model
Description
Details
Author(s)
References
Description
Uses a particle marginal Metropolis-Hastings (PMMH) algorithm to sample from the posterior distribution of the environmental and transmission parameters of a hidden SIRS model given observed cholera data.
Details
Package: bayessir
Type: Package
Version: 1.0
Date: 2014-01-09
License: GPL-3
Main algorithm and example: bayessir
Author(s)
Amanda Koepke and Vladimir Minin
Maintainer: Amanda Koepke <alallen@stat.washington.edu>
References
Andrieu, Christophe, Arnaud Doucet, and Roman Holenstein. "Particle Markov chain Monte Carlo methods." Journal of the Royal Statistical Society: Series B (Statistical Methodology) 72.3 (2010): 269-342.
vnminin/bayessir documentation built on May 3, 2019, 6:17 p.m.
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Description Details Author(s) References
Description
Uses a particle marginal Metropolis-Hastings (PMMH) algorithm to sample from the posterior distribution of the environmental and transmission parameters of a hidden SIRS model given observed cholera data.
Details
| Package: | bayessir |
| Type: | Package |
| Version: | 1.0 |
| Date: | 2014-01-09 |
| License: | GPL-3 |
Main algorithm and example: bayessir
Author(s)
Amanda Koepke and Vladimir Minin
Maintainer: Amanda Koepke <alallen@stat.washington.edu>
References
Andrieu, Christophe, Arnaud Doucet, and Roman Holenstein. "Particle Markov chain Monte Carlo methods." Journal of the Royal Statistical Society: Series B (Statistical Methodology) 72.3 (2010): 269-342.
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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