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Composite Likelihood Methods Based on Minimum Density Power Divergence Estimator

In this paper, a robust version of the Wald test statistic for composite likelihood is considered by using the composite minimum density power divergence estimator instead of the composite maximum likelihood estimator. This new family of test statistics will be called Wald-type test statistics. The...

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Detalles Bibliográficos
Autores principales: Castilla, Elena, Martín, Nirian, Pardo, Leandro, Zografos, Konstantinos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512195/
https://www.ncbi.nlm.nih.gov/pubmed/33265108
http://dx.doi.org/10.3390/e20010018
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author Castilla, Elena
Martín, Nirian
Pardo, Leandro
Zografos, Konstantinos
author_facet Castilla, Elena
Martín, Nirian
Pardo, Leandro
Zografos, Konstantinos
author_sort Castilla, Elena
collection PubMed
description In this paper, a robust version of the Wald test statistic for composite likelihood is considered by using the composite minimum density power divergence estimator instead of the composite maximum likelihood estimator. This new family of test statistics will be called Wald-type test statistics. The problem of testing a simple and a composite null hypothesis is considered, and the robustness is studied on the basis of a simulation study. The composite minimum density power divergence estimator is also introduced, and its asymptotic properties are studied.
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spelling pubmed-75121952020-11-09 Composite Likelihood Methods Based on Minimum Density Power Divergence Estimator Castilla, Elena Martín, Nirian Pardo, Leandro Zografos, Konstantinos Entropy (Basel) Article In this paper, a robust version of the Wald test statistic for composite likelihood is considered by using the composite minimum density power divergence estimator instead of the composite maximum likelihood estimator. This new family of test statistics will be called Wald-type test statistics. The problem of testing a simple and a composite null hypothesis is considered, and the robustness is studied on the basis of a simulation study. The composite minimum density power divergence estimator is also introduced, and its asymptotic properties are studied. MDPI 2017-12-31 /pmc/articles/PMC7512195/ /pubmed/33265108 http://dx.doi.org/10.3390/e20010018 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Castilla, Elena
Martín, Nirian
Pardo, Leandro
Zografos, Konstantinos
Composite Likelihood Methods Based on Minimum Density Power Divergence Estimator
title Composite Likelihood Methods Based on Minimum Density Power Divergence Estimator
title_full Composite Likelihood Methods Based on Minimum Density Power Divergence Estimator
title_fullStr Composite Likelihood Methods Based on Minimum Density Power Divergence Estimator
title_full_unstemmed Composite Likelihood Methods Based on Minimum Density Power Divergence Estimator
title_short Composite Likelihood Methods Based on Minimum Density Power Divergence Estimator
title_sort composite likelihood methods based on minimum density power divergence estimator
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512195/
https://www.ncbi.nlm.nih.gov/pubmed/33265108
http://dx.doi.org/10.3390/e20010018
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