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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
Descripción
Sumario: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.