sports

This data set is due to Louis Roussos who asked 130 students at the
University of Illinois to rank seven sports according to their preference in participating:
 A = Baseball, B = Football, C = Basketball, D = Tennis, E = Cycling, F =
 Swimming, G = Jogging.

datasets

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

sports function

A list containing:<dl>
 <dt>data</dt>
<dd>a matrix containing 130 ranks of size 7 in ranking representation.
The ranking representation r=(r_1,...,r_m) contains the ranks assigned to the objects, and means that
the ith object is in r_ith position.
For example, if the ranking representation of a rank is (4,3,1,2,5), it means that judge ranks the first
object in 4th position, second object in 3rd position, ...</dd>
 <dt>frequency</dt>
<dd>a matrix with 123 different ranks of size 7. In each row the first 7 columns correspond to one
observed ranking and the last column contains the observation frequency.</dd> <dt>m</dt>
<dd>the size of the rankings (m=7).</dd>
</dl>

Format

Rank data: sports — sports

A list containing:<dl>
 <dt>data</dt>
<dd>a matrix containing 130 ranks of size 7 in ranking representation.
The ranking representation r=(r_1,...,r_m) contains the ranks assigned to the objects, and means that
the ith object is in r_ith position.
For example, if the ranking representation of a rank is (4,3,1,2,5), it means that judge ranks the first
object in 4th position, second object in 3rd position, ...</dd>


 <dt>frequency</dt>
<dd>a matrix with 123 different ranks of size 7. In each row the first 7 columns correspond to one
observed ranking and the last column contains the observation frequency.</dd>

 <dt>m</dt>
<dd>the size of the rankings (m=7).</dd>


</dl>

sports: Rank data: sports

Description

Arguments

Format

See Also

Examples