In this paper, we propose preliminary estimators for the parameters of a mixture distribution introduced for the analysis of ordinal data where the mixture components are given by a Combination of a discrete Uniform and a shifted Binomial distribution (cub model). After reviewing some preliminary concepts related to the meaning of parameters which characterize such models, we introduce estimators which are related to the location and heterogeneity of the observed distributions, respectively, in order to accelerate the EM procedure for the maximum likelihood estimation. A simulation experiment has been performed to investigate their main features and to confirm their usefulness. A check of the proposal on real case studies and some comments conclude the paper. © 2012 Springer-Verlag.

Preliminary estimators for a mixture model of ordinal data / Iannario, Maria. - In: ADVANCES IN DATA ANALYSIS AND CLASSIFICATION. - ISSN 1862-5347. - 6:3(2012), pp. 163-184. [10.1007/s11634-012-0111-5]

Preliminary estimators for a mixture model of ordinal data

IANNARIO, MARIA
2012

Abstract

In this paper, we propose preliminary estimators for the parameters of a mixture distribution introduced for the analysis of ordinal data where the mixture components are given by a Combination of a discrete Uniform and a shifted Binomial distribution (cub model). After reviewing some preliminary concepts related to the meaning of parameters which characterize such models, we introduce estimators which are related to the location and heterogeneity of the observed distributions, respectively, in order to accelerate the EM procedure for the maximum likelihood estimation. A simulation experiment has been performed to investigate their main features and to confirm their usefulness. A check of the proposal on real case studies and some comments conclude the paper. © 2012 Springer-Verlag.
2012
Preliminary estimators for a mixture model of ordinal data / Iannario, Maria. - In: ADVANCES IN DATA ANALYSIS AND CLASSIFICATION. - ISSN 1862-5347. - 6:3(2012), pp. 163-184. [10.1007/s11634-012-0111-5]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/511478
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