lgmm.theta: MLE for theta - Generalized Mallows Model

In PerMallows: Permutations and Mallows Distributions

MLE for theta - Generalized Mallows Model

Description

Compute the MLE for the dispersion parameter (theta) given a sample of n permutations and a central permutation

Usage

lgmm.theta(
  data,
  sigma_0 = identity.permutation(dim(data)[2]),
  dist.name = "kendall"
)

Arguments

data	the matrix with the permutations to estimate
sigma_0	optional the initial guess for the consensus permutation. If not given it is assumed to be the identity permutation
dist.name	optional name of the distance used by the GMM. One of: kendall (default), cayley, hamming

Value

The MLE for the dispersion parameter

Examples

data <- matrix(c(1,2,3,4, 1,4,3,2, 1,2,4,3), nrow = 3, ncol = 4, byrow = TRUE)
lgmm.theta(data, dist.name="kendall")
lgmm.theta(data, dist.name="cayley")
lgmm.theta(data, dist.name="cayley", sigma_0=c(1,4,3,2))
lgmm.theta(data, dist.name="hamming")

PerMallows documentation built on April 3, 2025, 11:09 p.m.