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, …)
is.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
mcmc.list,
mcmcUpgrade,
thin,
window.mcmc,
summary.mcmc,
plot.mcmc.