R: Markov Chain Monte Carlo Objects

mcmc {coda} | R Documentation

## Markov Chain Monte Carlo Objects

### Description

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`.

### Usage

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

### Arguments

`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

### Note

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.

### Author(s)

Martyn Plummer

### See Also

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

[Package coda version 0.19-1 Index]