Assessing Similarity of Rating Distributions by Kullback-Leibler Divergence

被引：10
|
作者：
Corduas, Marcella [1 ]
机构：
[1] Univ Naples Federico 2, Dipartimento Sci Stat, I-80138 Naples, Italy
来源：
CLASSIFICATION AND MULTIVARIATE ANALYSIS FOR COMPLEX DATA STRUCTURES | 2011年
关键词：
PREFERENCES;
D O I：
10.1007/978-3-642-13312-1_22
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A mixture model for ordinal data modelling (denoted CUB) has been recently proposed in literature. Specifically, ordinal data are represented by means of a discrete random variable which is a mixture of a Uniform and shifted Binomial random variables. This article proposes a testing procedure based on the Kullback-Leibler divergence in order to compare CUB models and detect similarities in the structure of judgements that raters express on set of items.
引用
收藏
页码：221 / 228
页数：8
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