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mcmc

Markov Chain Monte Carlo

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, <doi:10.1214/12-AOS1048>, function morph.metrop), which achieves geometric ergodicity by change of variable.

Functions (8)

mcmc

Markov Chain Monte Carlo

v0.9-7
MIT + file LICENSE
Authors
Charles J. Geyer <charlie@stat.umn.edu> and Leif T. Johnson <ltjohnson@google.com>
Initial release
2020-03-20

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