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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/14817

Title: Permutation inference for a class of mixture models
Authors: Bonnini, Stefano
Piccolo, Domenico
Salmaso, Luigi
Solmi, Francesca
Issue Date: 2012
Citation: COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 41 (16-17), p. 2879-2895
Abstract: In statistical surveys, people are often asked to express evaluations on several topics or to make an ordered arrangement in a list of objects (items, services, sentences, etc.); thus, the analysis of ratings and rankings is receiving a growing interest in many fields. In this framework, we develop a testing procedure for a class of mixture models with covariates (defined as CUB models), proposed by Picollo (2003) and D'Elia and Piccolo (2005) and generally developed in a parametric context. Instead, we propose a nonparametric solution to perform inference on CUB models, specifically on the coefficients of the covariates. A simulation study proves that this approach is more appropriate in some specific data settings, mostly for small sample sizes.
URI: http://hdl.handle.net/1942/14817
DOI: 10.1080/03610926.2011.590915
ISI #: 000308465100005
ISSN: 0361-0926
Category: A1
Type: Journal Contribution
Appears in Collections: Research publications

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