asymptotic_partition_function: Asymptotic Approximation of Partition Function

In BayesMallows: Bayesian Preference Learning with the Mallows Rank Model

Asymptotic Approximation of Partition Function

Description

Compute the asymptotic approximation of the logarithm of the partition function, using the iteration algorithm of \insertCitemukherjee2016;textualBayesMallows.

Usage

asymptotic_partition_function(
  alpha_vector,
  n_items,
  metric,
  K,
  n_iterations = 1000L,
  tol = 1e-09
)

Arguments

alpha_vector	A numeric vector of alpha values.
n_items	Integer specifying the number of items.
metric	One of "footrule" and "spearman".
K	Integer.
n_iterations	Integer specifying the number of iterations.
tol	Stopping criterion for algorithm. The previous matrix is subtracted from the updated, and if the maximum absolute relative difference is below tol, the iteration stops.

Value

A vector, containing the partition function at each value of alpha.

References

\insertAllCited

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