The Metropolis Algorithm
Convert glm_metropolis output to mcmc object from package coda
Inverse logit transform
logistic log likelihood
metropolis.control
Use the Metropolis Hastings algorithm to estimate Bayesian glm paramet...
Gaussian log likelihood
Plot the output from the metropolis function
Print a metropolis.samples object
Summarize a probability distribution from a Markov Chain
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>.