summary

summary,Rankclust-method

output object from <code><a rd-options="" href="/link/rankclust?package=Rankcluster&version=0.94.1" data-mini-rdoc="Rankcluster::rankclust">rankclust</a></code>.

object

This function This function gives the summary of output from <code>rankclust</code>.

Implementation of a model-based clustering algorithm for
ranking data (C. Biernacki, J. Jacques (2013) <doi:10.1016/j.csda.2012.08.008>).
Multivariate rankings as well as partial rankings are taken
into account. This algorithm is based on an extension of the Insertion
Sorting Rank (ISR) model for ranking data, which is a meaningful and
effective model parametrized by a position parameter (the modal ranking,
quoted by mu) and a dispersion parameter (quoted by pi). The heterogeneity
of the rank population is modelled by a mixture of ISR, whereas conditional
independence assumption is considered for multivariate rankings.

Quentin Grimonprez

Rankcluster

Model-Based Clustering for Multivariate Partial Ranking Data

Julien Jacques

Christophe Biernacki

summary function

output object from <code><a rd-options='' href='rankclust'>rankclust</a></code>.

summary: summary function.

Description

Usage

Arguments