Update MCMC Clustering Procedure — update.sfclust • sfclust

This function continues the MCMC sampling of a sfclust object based on previous results or update the model fitting for a specified sample clustering if the argument sample is provided.

Usage

# S3 method for class 'sfclust'
update(
  object,
  niter = NULL,
  burnin = 0,
  thin = 1,
  nmessage = 10,
  sample = NULL,
  path_save = NULL,
  nsave = nmessage,
  ...
)

Arguments

object: A sfclust object.
niter: An integer specifying the number of additional MCMC iterations to perform. If NULL (default), no additional iterations are run and the within-cluster INLA models are refitted for the current clustering sample.
burnin: An integer specifying the number of burn-in iterations to discard.
thin: An integer specifying the thinning interval for recording results.
nmessage: An integer specifying the number of messages to display during the process.
sample: An integer specifying the clustering sample number to be executed. The default is the last sample (i.e., nrow(x$samples$membership)).
path_save: A character string specifying the file path to save the results. If NULL, results are not saved.
nsave: An integer specifying how often to save results. Defaults to nmessage.
...: Additional arguments (currently not used).

Value

An updated sfclust object with (i) new clustering samples if sample is not specified, or (ii) updated within-cluster model results if sample is given.

Details

This function takes the last state of the Markov chain from a previous sfclust_fit / sfclust execution and uses it as the starting point for additional MCMC iterations. If niter = NULL (the default), no additional iterations are run; instead, the within-cluster INLA models are fitted for the clustering given by sample (or the current clust$id if sample is NULL). This is useful when loading a checkpoint saved during a run, where the models were not yet stored: result <- update(result).