An EM algorithm to fit Mallows' Models to full or partial rankings, with or without ties.
|Date of publication||2012-02-21 17:27:29|
|License||GPL (>= 2)|
AllKendall: All Kendall's distances between two sets of rankings.
AllSeqDists: Calculate all distances between a set of sequences and a...
BestFit: Fit Mallows model N times and select most likely model. The...
C_lam: Calculate the normalizing coefficient for Mallow's model in a...
ConstructSeqs: Constructs sequences from Kendall Information matricies.
datas: Sample data set.
DistanceDistribution: Calculate the Kendall distance distribution in N! space.
elect: 1980 APA Presidential Candidate ranking data.
EStep: The Expectation step of the EM algorithm.
FormatOut: Formats the data in the "Solve" function for output.
KendallInfo: All information used to calculate Kendall's distance.
Lambda: Objective function to determine lambda.
Likelihood: Likelihood of the data and parameters.
Mallows: Fits a Multi-Modal Mallows' model to ranking data.
NextTable: Calculates the table of Kendall distances in (N+1)! space,...
Rgen: Initialize sequence modes for the clustering process.
RMallow-package: Fit Multi-modal Mallows' models to ranking data.
SeqDistribution: Calculates distances in N! space.
SimplifySequences: Change the form of ordered sequences.
three.mode: Fitted version of the toy datas data set, with three modal...
two.mode: Two-mode Mallows' model fit to toy data set "datas"
two.seq: Bi-modal Mallow's model fit to the APA data set.
UpdateLambda: Update the Lambda parameters of clusters.
UpdateP: Update Proportion in each cluster.
UpdateR: Update modal sequences in each cluster.