mcmc (0.9-4)

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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, Annals of Statistics, 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 over 1 year ago.


9 previous versions

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