Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10328139 | Computational Statistics & Data Analysis | 2005 | 18 Pages |
Abstract
A mixture model for preferences data, which adequately represents the composite nature of the elicitation mechanism in ranking processes, is proposed. Both probabilistic features of the mixture distribution and inferential and computational issues arising from the maximum likelihood parameters estimation are addressed. Moreover, empirical evidence from different data sets confirming the goodness of fit of the proposed model to many real preferences data is shown.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Angela D'Elia, Domenico Piccolo,