Estimation.RUM.MLE: Performs parameter estimation for a Random Utility Model with...

In StatRank: Statistical Rank Aggregation: Inference, Evaluation, and Visualization

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")

StatRank documentation built on May 1, 2019, 8:22 p.m.