set_model_options {BayesMallows}

Set options for Bayesian Mallows model

Description

Specify various model options for the Bayesian Mallows model.

Usage

set_model_options(
  metric = c("footrule", "spearman", "cayley", "hamming", "kendall", "ulam"),
  n_clusters = 1,
  error_model = c("none", "bernoulli")
)

Arguments

metric

A character string specifying the distance metric to use in the Bayesian Mallows Model. Available options are "footrule", "spearman", "cayley", "hamming", "kendall", and "ulam". The distance given by metric is also used to compute within-cluster distances, when include_wcd = TRUE.

n_clusters

Integer specifying the number of clusters, i.e., the number of mixture components to use. Defaults to 1L, which means no clustering is performed. See compute_mallows_mixtures() for a convenience function for computing several models with varying numbers of mixtures.

error_model

Character string specifying which model to use for inconsistent rankings. Defaults to "none", which means that inconsistent rankings are not allowed. At the moment, the only available other option is "bernoulli", which means that the Bernoulli error model is used. See Crispino et al. (2019) for a definition of the Bernoulli model.

Value

An object of class "BayesMallowsModelOptions", to be provided in the model_options argument to compute_mallows(), compute_mallows_mixtures(), or update_mallows().

References

Crispino M, Arjas E, Vitelli V, Barrett N, Frigessi A (2019). “A Bayesian Mallows approach to nontransitive pair comparison data: How human are sounds?” The Annals of Applied Statistics, 13(1), 492–519. doi:10.1214/18-aoas1203.

See Also

Other preprocessing: get_transitive_closure(), set_compute_options(), set_initial_values(), set_priors(), set_progress_report(), set_smc_options(), setup_rank_data()