mcmc-utilities | R Documentation |

`mcmc.list`

objects`colMeans.mcmc.list`

is a "method" for (non-generic) `colMeans()`

applicable to `mcmc.list`

objects.

`var.mcmc.list`

is a "method" for (non-generic)
`var()`

applicable to `mcmc.list`

objects. Since MCMC chains
are assumed to all be sampling from the same underlying
distribution, their pooled mean is used.

`sweep.mcmc.list`

is a "method" for (non-generic)
`sweep()`

applicable to `mcmc.list`

objects.

`lapply.mcmc.list`

is a "method" for (non-generic)
`lapply()`

applicable to `mcmc.list`

objects.

```
colMeans.mcmc.list(x, ...)
var.mcmc.list(x, ...)
sweep.mcmc.list(x, STATS, FUN = "-", check.margin = TRUE, ...)
lapply.mcmc.list(X, FUN, ...)
```

`x` |
a |

`...` |
additional arguments to the functions evaluated on each chain. |

`STATS` , `FUN` , `check.margin` |
See help for |

`X` |
An |

These implementations should be equivalent (within
numerical error) to the same function being called on
`as.matrix(x)`

, while avoiding construction of the large matrix.

`colMeans.mcmc`

returns a vector with length equal to
the number of mcmc chains in `x`

with the mean value for
each chain.

`sweep.mcmc.list`

returns an appropriately modified
version of `x`

`lapply.mcmc.list`

returns an `mcmc.list`

each of
whose chains had been passed through `FUN`

.

`mcmc.list`

`colMeans()`

`var()`

`sweep()`

`lapply()`

```
data(line, package="coda")
colMeans(as.matrix(line)) # also coda
colMeans.mcmc.list(line) # "Method"
data(line, package="coda")
var(as.matrix(line)) # coda
var.mcmc.list(line) # "Method"
data(line, package="coda")
colMeans.mcmc.list(line)-1:3
colMeans.mcmc.list(sweep.mcmc.list(line, 1:3))
data(line, package="coda")
colMeans.mcmc.list(line)[c(2,3,1)]
colMeans.mcmc.list(lapply.mcmc.list(line, `[`,,c(2,3,1)))
```

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