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, ...) is.mcmc(x)
data |
a vector or matrix of MCMC output |
start |
the iteration number of the first observation |
end |
the iteration number of the last observation |
thin |
the thinning interval between consecutive observations |
x |
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
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