Estimation.RUM.MLE {StatRank}

Performs parameter estimation for a Random Utility Model with different noise distributions

Description

This function supports RUMs 1) Normal 2) Normal with fixed variance (fixed at 1) 3) Exponential (top k setting like Election)

Usage

Estimation.RUM.MLE(Data, iter = 10, dist, race = FALSE)

Arguments

Data

data in either partial or full rankings

iter

number of EM iterations to run

dist

underlying distribution. Can be "norm", "norm.fixedvariance", "exp"

race

indicator that each agent chose a random subset of alternatives to compare

Value

parameters of the latent RUM distributions

Examples

Data.Tiny <- matrix(c(1, 2, 3, 3, 2, 1, 1, 2, 3), ncol = 3, byrow = TRUE)
Estimation.RUM.MLE(Data.Tiny, iter = 2, dist="norm")