[,Rankclust-method

object from which to extract element(s) or in which to replace element(s).

the number of cluster of the element we want to extract.

This is overloading of square braces to extract values of various 
slots of the output from the function <code><a rd-options="" href="/link/rankclust?package=Rankcluster&version=0.94.1" data-mini-rdoc="Rankcluster::rankclust">rankclust</a></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

[ function

This is overloading of square braces to extract values of various 
slots of the output from the function <code><a rd-options='' href='rankclust'>rankclust</a></code>.

[: Getter method for rankclust output

Description

Usage

Arguments