Description Usage Arguments Details Value Examples

This function retrieves the number of chains used for an MCMC simulation.

Reset number of starting values

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ```
nStarts(object)
nStarts(object) <- value
## S4 method for signature 'McmcParams'
nStarts(object)
## S4 replacement method for signature 'McmcParams'
nStarts(object) <- value
## S4 method for signature 'MixtureModel'
nStarts(object)
## S4 replacement method for signature 'MixtureModel'
nStarts(object) <- value
``` |

`object` |
see |

`value` |
new number of chains |

Simulating starting values from the priors makes it imperative to
run a large nubmer of simulations for burnin and to carefully evaluate the
chains following burning for convergence. The adequacy of the burnin is
difficult to assess in high-dimensional settings with a large number of
CNPs. To avoid starting in regions of low posterior probabilitiy, we use
existing EM-based methods in the package `{mclust}`

to select starting
values from `N`

bootstrap sample of the observed data, where `N`

is specificed as in the example below. For each bootstrap sample, starting
values for the model are estimated. For each set of simulated starting
values, the log likelihood of the full data is evaluated. The starting
values with the largest log likelihood are used as initial values for the
MCMC simulations.

An integer of the number of different starts.

1 2 3 | ```
number_of_chains <- nStarts(SingleBatchModelExample)
number_of_chains <- 10
nStarts(SingleBatchModelExample) <- number_of_chains
``` |

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