McmcParams-class {CNPBayes} | R Documentation

## An object to specify MCMC options for a later simulation

### Description

An object to specify MCMC options for a later simulation

### Slots

`thin`

  A one length numeric to specify thinning. A value of n indicates that every nth sample should be saved. Thinning helps to reduce autocorrelation.

`iter`

  A one length numeric to specify how many MCMC iterations should be sampled.

`burnin`

  A one length numeric to specify burnin. The first $n$ samples will be discarded.

`nstarts`

  A one length numeric to specify the number of chains in a simulation.

`param_updates`

  Indicates whether each parameter should be updated (1) or fixed (0).

`min_GR`

  minimum value of multivariate Gelman Rubin statistic for diagnosing convergence. Default is 1.2.

`min_effsize`

  the minimum mean effective size of the chains. Default is 1/3 * iter.

`max_burnin`

  The maximum number of burnin iterations before we give up and return the existing model.

`min_chains`

  minimum number of independence MCMC chains used for assessing convergence. Default is 3.

### Examples

    McmcParams()
    McmcParams(iter=1000)
    mp <- McmcParams()
    iter(mp)

[Package CNPBayes version 1.13.5 Index]