burnin-set: Set the burnin

In BayesMallows: Bayesian Preference Learning with the Mallows Rank Model

Set the burnin

Description

Set or update the burnin of a model computed using Metropolis-Hastings.

Usage

burnin(model, ...) <- value

## S3 replacement method for class 'BayesMallows'
burnin(model, ...) <- value

## S3 replacement method for class 'BayesMallowsMixtures'
burnin(model, ...) <- value

Arguments

model	An object of class BayesMallows returned from compute_mallows() or an object of class BayesMallowsMixtures returned from compute_mallows_mixtures().
...	Optional arguments passed on to other methods. Currently not used.
value	An integer specifying the burnin. If model is of class BayesMallowsMixtures, a single value will be assumed to be the burnin for each model element. Alternatively, value can be specified as an integer vector of the same length as model, and hence a separate burnin can be set for each number of mixture components.

Value

An object of class BayesMallows with burnin set.

See Also

Other modeling: burnin(), compute_mallows(), compute_mallows_mixtures(), compute_mallows_sequentially(), sample_prior(), update_mallows()

Examples

set.seed(445)
mod <- compute_mallows(setup_rank_data(potato_visual))
assess_convergence(mod)
burnin(mod)
burnin(mod) <- 1500
burnin(mod)
plot(mod)
#'
models <- compute_mallows_mixtures(
  data = setup_rank_data(cluster_data),
  n_clusters = 1:3)
burnin(models)
burnin(models) <- 100
burnin(models)
burnin(models) <- c(100, 300, 200)
burnin(models)

BayesMallows documentation built on Sept. 11, 2024, 5:31 p.m.