Variable selection in finite mixture of regression models using the skew-normal distribution
© 2019 Informa UK Limited, trading as Taylor & Francis Group.
| Publié dans: | Journal of applied statistics. - 1991. - 47(2020), 16 vom: 17., Seite 2941-2960 |
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| Auteur principal: | |
| Autres auteurs: | , |
| Format: | Article en ligne |
| Langue: | English |
| Publié: |
2020
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| Accès à la collection: | Journal of applied statistics |
| Sujets: | Journal Article 62F35 62H30 62J07 Hard LASSO SCAD Variable selection mixture regression models skew-normal distribution |
| Résumé: | © 2019 Informa UK Limited, trading as Taylor & Francis Group. Variable selection in finite mixture of regression (FMR) models is frequently used in statistical modeling. The majority of applications of variable selection in FMR models use a normal distribution for regression error. Such assumptions are unsuitable for a set of data containing a group or groups of observations with asymmetric behavior. In this paper, we introduce a variable selection procedure for FMR models using the skew-normal distribution. With appropriate choice of the tuning parameters, we establish the theoretical properties of our procedure, including consistency in variable selection and the oracle property in estimation. To estimate the parameters of the model, a modified EM algorithm for numerical computations is developed. The methodology is illustrated through numerical experiments and a real data example |
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| Description: | Date Revised 16.07.2022 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
| ISSN: | 0266-4763 |
| DOI: | 10.1080/02664763.2019.1709051 |