R: Replicated Markov Chain Monte Carlo Objects

mcmc.list {coda} | R Documentation

## Replicated Markov Chain Monte Carlo Objects

### Description

The function ‘mcmc.list’ is used to represent parallel runs of the same chain, with different starting values and random seeds. The list must be balanced: each chain in the list must have the same iterations and the same variables.

Diagnostic functions which act on `mcmc` objects may also be applied to `mcmc.list` objects. In general, the chains will be combined, if this makes sense, otherwise the diagnostic function will be applied separately to each chain in the list.

Since all the chains in the list have the same iterations, a single time dimension can be ascribed to the list. Hence there are time series methods `time`, `window`, `start`, `end`, `frequency` and `thin` for `mcmc.list` objects.

An `mcmc.list` can be indexed as if it were a single mcmc object using the `[` operator (see examples below). The `[[` operator selects a single `mcmc` object from the list.

### Usage

    mcmc.list(...)
    as.mcmc.list(x, ...)
    is.mcmc.list(x)

### Arguments

`...` | a list of mcmc objects
`x` | an object that may be coerced to mcmc.list

### Author(s)

Martyn Plummer

### See Also

`mcmc`.

### Examples

    data(line)
    x1 <- line[[1]]                    #Select first chain
    x2 <- line[,1, drop=FALSE]         #Select first var from all chains
    varnames(x2) == varnames(line)[1]  #TRUE

[Package coda version 0.19-1 Index]