Set the burnin

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

Usage

burnin(model, ...) <- value

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

# S3 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)
#> NULL
burnin(mod) <- 1500
burnin(mod)
#> [1] 1500
plot(mod)

#'
models <- compute_mallows_mixtures(
  data = setup_rank_data(cluster_data),
  n_clusters = 1:3)
burnin(models)
#> [[1]]
#> NULL
#> 
#> [[2]]
#> NULL
#> 
#> [[3]]
#> NULL
#> 
burnin(models) <- 100
burnin(models)
#> [[1]]
#> [1] 100
#> 
#> [[2]]
#> [1] 100
#> 
#> [[3]]
#> [1] 100
#> 
burnin(models) <- c(100, 300, 200)
burnin(models)
#> [[1]]
#> [1] 100
#> 
#> [[2]]
#> [1] 300
#> 
#> [[3]]
#> [1] 200
#>