Description Objects from the Class Slots Methods Author(s) See Also Examples

This class holds tuning parameters for the Metropolis-Hastings and Wang-Landau algorithms.

Objects can be created by calls of the function `"tuningparameters"`

.

`nchains`

:Object of class

`"numeric"`

: it should be an integer representing the desired number of parallel chains.`niterations`

:Object of class

`"numeric"`

: it should be an integer representing the desired number of iterations.`computemean`

:Object of class

`"logical"`

: specifies whether the mean of all chains should be computed at each iteration (useful if the chains are not to be stored).`computemeanburnin`

:Object of class

`"numeric"`

: if`computemean`

is set to TRUE, specifies after which iteration the mean of the chain has to be computed. Default is 0 (no burnin).`saveeverynth`

:Object of class

`"numeric"`

: specifies when the chains are to be stored: for instance at every iteration (=1), every 10th iteration (=10), etc. Default is -1, meaning the chains are not stored.

- show
`signature(object = "tuningparameters")`

: provides a little summary of a binning object when called (or when`print`

is called).

Luke Bornn <[email protected]>, Pierre E. Jacob <[email protected]>

`adaptiveMH`

`preexplorationAMH`

`pawl`

1 2 | ```
showClass("tuningparameters")
mhparameters <- tuningparameters(nchains = 10, niterations = 1000, adaptiveproposal = TRUE)
``` |

PAWL documentation built on May 29, 2017, 7:03 p.m.

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.