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New families of estimators and test statistics in log-linear models

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Martín Apaolaza, Níriam y Pardo Llorente, Leandro (2008) New families of estimators and test statistics in log-linear models. Journal of multivariate analysis, 99 (8). pp. 1590-1609. ISSN 0047-259X

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URL Oficial: http://www.sciencedirect.com/science/article/pii/S0047259X08000171


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In this paper we consider categorical data that are distributed according to a multinomial, product-multinomial or Poisson distribution whose expected values follow a log-linear model and we study the inference problem of hypothesis testing in a log-linear model setting. The family of test statistics considered is based on the family of phi-divergence measures. The unknown parameters in the log-linear model under consideration are also estimated using phi-divergence measures: Minimum phi-divergence estimators. A simulation study is included to find test statistics that offer an attractive alternative to the Pearson chi-square and likelihood-ratio test statistics.


Tipo de documento:Artículo
Palabras clave:asymptotic distributions; nested hypotheses; Poisson sampling; multinomial sampling; product-multinomial sampling; minimum phi-divergence estimator; phi-divergence test statistics; Loglinear models.
Materias:Ciencias > Matemáticas > Estadística matemática
Código ID:17534
Depositado:21 Dic 2012 11:27
Última Modificación:25 Jul 2018 11:11

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