metropolis: The Metropolis Algorithm

Learning and using the Metropolis algorithm for Bayesian fitting of a generalized linear model. The package vignette includes examples of hand-coding a logistic model using several variants of the Metropolis algorithm. The package also contains R functions for simulating posterior distributions of Bayesian generalized linear model parameters using guided, adaptive, guided-adaptive and random walk Metropolis algorithms. The random walk Metropolis algorithm was originally described in Metropolis et al (1953) <doi:10.1063/1.1699114>.

Version: 0.1.5
Depends: coda, R (≥ 3.5.0)
Imports: stats
Suggests: knitr
Published: 2020-01-23
Author: Alexander Keil [aut, cre]
Maintainer: Alexander Keil <akeil at unc.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Language: en-US
Materials: README NEWS
CRAN checks: metropolis results

Downloads:

Reference manual: metropolis.pdf
Vignettes: The metropolis algorithm for fitting Bayesian GLMs
Package source: metropolis_0.1.5.tar.gz
Windows binaries: r-devel: metropolis_0.1.5.zip, r-devel-gcc8: metropolis_0.1.5.zip, r-release: metropolis_0.1.5.zip, r-oldrel: metropolis_0.1.5.zip
OS X binaries: r-release: metropolis_0.1.5.tgz, r-oldrel: metropolis_0.1.5.tgz

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