summary,Rankclust-method

This function gives the summary of an 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,Rankclust-method function

<dl><dt>object</dt>
<dd>output object from <code>rankclust</code>.</dd>
<dt>...</dt>
<dd>Not used.</dd></dl>

Arguments

Summary function. — summary,Rankclust-method

<dl>

<dt>object</dt>
<dd>output object from <code>rankclust</code>.</dd>


<dt>...</dt>
<dd>Not used.</dd>

</dl>

summary,Rankclust-method: Summary function.

Description

Usage

Arguments