mcmc: Markov Chain Monte Carlo Objects

mcmcR Documentation

Markov Chain Monte Carlo Objects


The function mcmc is used to create a Markov Chain Monte Carlo object. The input data are taken to be a vector, or a matrix with one column per variable.

If the optional arguments start, end, and thin are omitted then the chain is assumed to start with iteration 1 and have thinning interval 1. If data represents a chain that starts at a later iteration, the first iteration in the chain should be given as the start argument. Likewise, if data represents a chain that has already been thinned, the thinning interval should be given as the thin argument.

An mcmc object may be summarized by the summary function and visualized with the plot function.

MCMC objects resemble time series (ts) objects and have methods for the generic functions time, start, end, frequency and window.


mcmc(data= NA, start = 1, end = numeric(0), thin = 1)
as.mcmc(x, ...)



a vector or matrix of MCMC output


the iteration number of the first observation


the iteration number of the last observation


the thinning interval between consecutive observations


An object that may be coerced to an mcmc object


Further arguments to be passed to specific methods


The format of the mcmc class has changed between coda version 0.3 and 0.4. Older mcmc objects will now cause is.mcmc to fail with an appropriate warning message. Obsolete mcmc objects can be upgraded with the mcmcUpgrade function.


Martyn Plummer

See Also

mcmc.list, mcmcUpgrade, thin, window.mcmc, summary.mcmc, plot.mcmc.

coda documentation built on May 29, 2024, 11:23 a.m.

Related to mcmc in coda...