compute_importance_sampling_estimate: Compute importance sampling estimates of log partition...

In BayesMallows: Bayesian Preference Learning with the Mallows Rank Model

Compute importance sampling estimates of log partition function for footrule and Spearman distances.

Description

Compute importance sampling estimates of log partition function for footrule and Spearman distances.

Usage

compute_importance_sampling_estimate(
  alpha_vector,
  n_items,
  metric = "footrule",
  nmc = 10000L
)

Arguments

alpha_vector	Vector of alpha values at which to compute partition function.
n_items	Integer specifying the number of ranked items.
metric	Distance measure of the target Mallows distribution. Defaults to footrule.
nmc	Number of Monte Carlo samples. Defaults to 1e4.

BayesMallows documentation built on Nov. 25, 2023, 5:09 p.m.