Estimation.RUM.Nonparametric: Nonparametric RUM Estimator

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

Description

Given rank data (full, top partial, or sub partial), this function returns an inference object that fits nonparametric latent utilties on the rank data.

Usage

Estimation.RUM.Nonparametric(Data, m, iter = 10, bw = 0.025,
  utilities.per.agent = 20, race = FALSE)

Arguments

Data	full, top partial, or sub partial rank data
m	number of alternatives
iter	number of EM iterations to run
bw	bandwidth, or smoothing parameter for KDE
utilities.per.agent	Number of utility vector samples that we get per agent. More generally gives a more accurate estimate
race	TRUE if data is sub partial, FALSE (default) if not

Examples

data(Data.Test)
Estimation.RUM.Nonparametric(Data.Test, m = 5, iter = 3)

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