Preliminary test estimators and phi-divergence measures in generalized linear models with binary data
We consider the problem of estimation of the parameters in Generalized Linear Models (GLM) with binary data when it is suspected that the parameter vector obeys some exact linear restrictions which are linearly independent with some degree of uncertainty. Based on minimum phi-divergence estimation (...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2008 |
| País: | España |
| Institución: | Universidad Complutense de Madrid (UCM) |
| Repositorio: | Docta Complutense |
| Idioma: | inglés |
| OAI Identifier: | oai:docta.ucm.es:20.500.14352/50252 |
| Acceso en línea: | https://hdl.handle.net/20.500.14352/50252 |
| Access Level: | acceso abierto |
| Palabra clave: | 519.2 phi-divergence measures Minimum phi-divergence estimator phi-divergence statistics Preliminary test estimator Contiguous alternative hypotheses Asymptotic bias Asymptotic quadratic risk. Estadística matemática (Matemáticas) 1209 Estadística |
| Sumario: | We consider the problem of estimation of the parameters in Generalized Linear Models (GLM) with binary data when it is suspected that the parameter vector obeys some exact linear restrictions which are linearly independent with some degree of uncertainty. Based on minimum phi-divergence estimation (M phi E), we consider some estimators for the parameters of the GLM: Unrestricted M phi E, restricted M phi E, Preliminary M phi E, Shrinkage M phi E, Shrinkage preliminary M phi E, James-Stein M phi E, Positive-part of Stein-Rule M phi E and Modified preliminary M phi E. Asymptotic bias as well as risk with a quadratic loss function are studied under contiguous alternative hypotheses. Some discussion about dominance among the estimators studied is presented. Finally, a simulation study is carried out. |
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