Fit Multi-Modal Mallows' Models to Ranking Data

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Documentation for package ‘RMallow’ version 1.1

• DESCRIPTION file.

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RMallow-package	Fit Multi-modal Mallows' models to ranking data.
AllKendall	All Kendall's distances between two sets of rankings.
AllSeqDists	Calculate all distances between a set of sequences and a fixed sequence.
BestFit	Fit Mallows model N times and select most likely model. The EM algorithm to fit Multi-Modal Mallows' models is prone to getting stuck in local maxima, so we run it several times and selec the best one.
ConstructSeqs	Constructs sequences from Kendall Information matricies.
C_lam	Calculate the normalizing coefficient for Mallow's model in a sequence space.
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.
hello	Hello, World!
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, given those in N! space.
Rgen	Initialize sequence modes for the clustering process.
RMallow	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 sequences.
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.