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: |
0.1.8 |
Depends: |
coda, R (≥ 3.5.0) |
Imports: |
stats |
Suggests: |
knitr, markdown |
Published: |
2020-09-21 |
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 |
Documentation:
Downloads:
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