Estimation.PL.MLE

data in either partial or full rankings
  (Partial rank case works for settings like car racing)

Data

iter


Performs parameter estimation for the Plackett-Luce model
using an Minorize Maximize algorithm


A set of methods to implement Generalized Method of Moments and Maximal
Likelihood methods for Random Utility Models. These methods are meant to
provide inference on rank comparison data. These methods accept full,
partial, and pairwise rankings, and provides methods to break down full or
partial rankings into their pairwise components. Please see Generalized
Method-of-Moments for Rank Aggregation from NIPS 2013 for a description of
some of our methods.

Estimation.PL.MLE: Performs parameter estimation for the Plackett-Luce model using an Minorize Maximize algorithm

Description

Usage

Arguments

Value

Examples