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); .


Reference manual

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0.1.8 by Alexander Keil, a year ago

Browse source code at

Authors: Alexander Keil [aut, cre]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports stats

Depends on coda

Suggests knitr, markdown

See at CRAN