Preliminary test estimators and phi-divergence measures in generalized linear models with binary data

dc.contributor.authorMenéndez Calleja, María Luisa
dc.contributor.authorPardo Llorente, Leandro
dc.contributor.authorPardo Llorente, María del Carmen
dc.date.accessioned2023-06-20T09:43:31Z
dc.date.available2023-06-20T09:43:31Z
dc.date.issued2008-11
dc.description.abstractWe 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.
dc.description.departmentDepto. de Estadística e Investigación Operativa
dc.description.facultyFac. de Ciencias Matemáticas
dc.description.refereedTRUE
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/17532
dc.identifier.doi10.1016/j.jmva.2008.02.011
dc.identifier.issn0047-259X
dc.identifier.officialurlhttp://www.sciencedirect.com/science/article/pii/S0047259X08000547
dc.identifier.relatedurlhttp://www.sciencedirect.com/
dc.identifier.urihttps://hdl.handle.net/20.500.14352/50252
dc.issue.number10
dc.journal.titleJournal of multivariate analysis
dc.language.isoeng
dc.page.final2284
dc.page.initial2265
dc.publisherAcademic Press
dc.relation.projectIDMTM2006-06872
dc.relation.projectIDUCM2007-910707
dc.rights.accessRightsopen access
dc.subject.cdu519.2
dc.subject.keywordphi-divergence measures
dc.subject.keywordMinimum phi-divergence estimator
dc.subject.keywordphi-divergence statistics
dc.subject.keywordPreliminary test estimator
dc.subject.keywordContiguous alternative hypotheses
dc.subject.keywordAsymptotic bias
dc.subject.keywordAsymptotic quadratic risk.
dc.subject.ucmEstadística matemática (Matemáticas)
dc.subject.unesco1209 Estadística
dc.titlePreliminary test estimators and phi-divergence measures in generalized linear models with binary data
dc.typejournal article
dc.volume.number99
dcterms.referencesS.M. Ali, S.D. Silvey, A general class of coefficients of divergence of one distribution from another, J. Roy. Statist. Soc. B 26 (1966) 131–142. T.A. Bancroft, On biases in estimation due to use of preliminary tests of significance, Ann. Math. Statist. 15 (1944) 190–204. N. Cressie, T.R.C. Read, Multinomial goodness-of-fit tests, J. Roy. Statist. Soc. B 46 (1984) 440–464. I. Csiszár, Eine Informationtheorestiche Ungleichung und ihre Anwendung anf den Beweis der Ergodizität Markoffshen Ketten. Publications of the Mathematical Institute of Hungarian Academy of Sciences, Series A, 8 (1963) 84–108. T.S. Ferguson, A course in large sample theory, in: Texts in Statistical Science, Chapman & Hall, New York, 1996. W. James, C. Stein, Estimation with quadratic loss, in: Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, University of California Press, Berkeley, CA, 1961, pp. 361–379. S. Kullback, Kullback information, in: S. Kotz, N.L. Johnson (Eds.), Encyclopedia of Statistical Sciences, vol. 4, John Wiley, New York, 1985, pp. 421–425. M.A. Matin, A.K. Md, E. Saleh, Some improved estimators in logistic regression model, J. Stat. Res. 39 (2) (2005) 37–58. MR2256551 M.A Matin, A.K. Md, E. Saleh, Small-sample properties of some improved estimators in logistic regression model with skew-normally distributed explanatory variables, J. Stat. Res. 40 (1) (2006) 1–21. P. McCullagh, J.A. Neider, Generalized Linear Models, second ed., Chapman and Hall, London, 1989. L. Pardo, Statistical Inference Based on Divergence Measures, Chapman & Hall/CRC, New York, 2006. J.A. Pardo, M.C. Pardo, Minimum phi-divergence estimators and phi-divergence statistics in GLM with binary data, Methodol. Comput. Appl. (2008), doi:10.1007/s11009-007-9054-2. A.K. Md, E. Saleh, P.K. Sen, Nonparametric estimation of location parameter after a preliminary test on regression, Ann. Statist. 6 (1978) 154–168. A.K. Md, E. Saleh, P.K. Sen, On shrinkage least-squares estimation in a parallelism problem, Comm. Statist. Theory Methods 15 (1986) 1451–1466. A.K. Md, E. Saleh, Theory of Preliminary Test and Stein-Type Estimation with Applications, Wiley, 2006. P.K. Sen, A.K. Md, E. Saleh, On preliminary test and shrinkage M-estimation in linear models, Ann. Statist. 15 (1987) 1580–1592. C. Stein, Inadmissibility of the usual estimator for the mean of a multivariate normal distribution, in: Proceedings of the Third Berkeley Symposium on Mathematical Statistics and Probability, vol. 1, University of California Press, Berkeley, CA, 1956, pp. 197–206. I. Vajda, Theory of Statistical Inference and Information, Kluwer, Boston, 1989.
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