print.metropolis.samples

<p>a "metropolis.samples" object from the function "metropolis_glm"</p>

<p>This function allows you to summarize output from the "metropolis_glm" function.</p>

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>.

Alexander Keil

print.metropolis.samples: Print a metropolis.samples object

Description

Usage

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Details