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: Castilla González, Elena María, Martín, Nirian, Pardo Llorente, Leandro, Zografos, Konstantinos
Tipo de recurso: artículo
Fecha de publicación:2017
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/19117
Acceso en línea:https://hdl.handle.net/20.500.14352/19117
Access Level:acceso abierto
Palabra clave:519.21
composite likelihood
maximum composite likelihood estimator
Wald test statistic
composite minimum density power divergence estimator
Wald-type test statistics
Probabilidades
Prueba de Wald
Matemáticas (Matemáticas)
Estadística matemática (Matemáticas)
Probabilidades (Matemáticas)
12 Matemáticas
1209 Estadística
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.