mcmc (0.9-5)

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Markov Chain Monte Carlo.

http://www.stat.umn.edu/geyer/mcmc/
https://github.com/cjgeyer/mcmc
http://cran.r-project.org/web/packages/mcmc

Simulates continuous distributions of random vectors using Markov chain Monte Carlo (MCMC). Users specify the distribution by an R function that evaluates the log unnormalized density. Algorithms are random walk Metropolis algorithm (function metrop), simulated tempering (function temper), and morphometric random walk Metropolis (Johnson and Geyer, 2012, , function morph.metrop), which achieves geometric ergodicity by change of variable.

Maintainer: Charles J. Geyer
Author(s): Charles J. Geyer <charlie@stat.umn.edu> and Leif T. Johnson <ltjohnson@google.com>

License: MIT + file LICENSE

Uses: xtable, Iso
Reverse depends: ltbayes, TBSSurvival, VarEff
Reverse suggests: ConnMatTools, pse, SamplerCompare

Released about 1 month ago.


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