lmm.theta: MLE for theta - Mallows Model

In PerMallows: Permutations and Mallows Distributions

MLE for theta - Mallows Model

Description

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

Usage

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

Arguments

data	the matrix with the permutations to estimate
sigma_0	optional the consensus permutation. If not given it is assumed to be the identity permutation
dist.name	optional the name of the distance used by the model. One of: kendall (default), cayley, hamming, ulam
disk	optional can only be true if estimating a MM under the Ulam distance. Insted of generating the whole set of SYT and count of permutations per distance, it loads the info from a file in the disk

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)
lmm.theta(data, dist.name="kendall")
lmm.theta(data, dist.name="cayley")
lmm.theta(data, dist.name="cayley", sigma_0=c(1,4,3,2))
lmm.theta(data, dist.name="hamming")
lmm.theta(data, dist.name="ulam")

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