words


The data was collected under the auspices of the Graduate Record
Examination Board. A sample of 98 college students were asked to rank five words according to strength of association (least to most associated) with the target word "Idea":
  A = Thought, B = Play, C = Theory, D = Dream and E = Attention.


datasets

Implementation of a model-based clustering algorithm for
ranking data. 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

words function

A list containing :
<dl>
  <dt>data</dt><dd>A matrix of size 98*5 containing the 98 answers. Each row corresponding to one ranking (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>matrix of size 15*6. Each row corresponds to one of the 15 different observed rankings, and the last column contains the observation frequency.</dd> <dt>m</dt><dd>the size of the rankings (m=5).</dd> </dl>

Format

M.A. Fligner and J.S. Verducci. "Distance based ranking models". J. Roy. Statist. Soc. Ser. B, 48(3):359-369, 1986.

words: rank data : words

Description

Arguments

Format

Source

Examples