tuningparameters: MCMC Tuning Parameters

In PAWL: Implementation of the PAWL algorithm

Description

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

Objects from the Class

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

Slots

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.

Methods

show

signature(object = "tuningparameters"): provides a little summary of a binning object when called (or when print is called).

Author(s)

Luke Bornn <[e-mail]>, Pierre E. Jacob <[e-mail]>

See Also

adaptiveMH preexplorationAMH pawl

Examples

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

PAWL documentation built on May 2, 2019, 5:58 a.m.