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

dc.contributor.authorMartín Apaolaza, Níriam
dc.contributor.authorPardo Llorente, Leandro
dc.date.accessioned2023-06-20T09:43:33Z
dc.date.available2023-06-20T09:43:33Z
dc.date.issued2008-09
dc.description.abstractIn 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.
dc.description.departmentSección Deptal. de Sistemas Informáticos y Computación
dc.description.facultyFac. de Ciencias Matemáticas
dc.description.refereedTRUE
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/17534
dc.identifier.doi10.1016/j.jmva.2008.01.002
dc.identifier.issn0047-259X
dc.identifier.officialurlhttp://www.sciencedirect.com/science/article/pii/S0047259X08000171
dc.identifier.relatedurlhttp://www.sciencedirect.com/
dc.identifier.urihttps://hdl.handle.net/20.500.14352/50253
dc.issue.number8
dc.journal.titleJournal of multivariate analysis
dc.language.isoeng
dc.page.final1609
dc.page.initial1590
dc.publisherAcademic Press
dc.relation.projectIDMTM2006-06872
dc.relation.projectIDUCM2006-910707
dc.rights.accessRightsrestricted access
dc.subject.cdu517.15
dc.subject.keywordasymptotic distributions
dc.subject.keywordnested hypotheses
dc.subject.keywordPoisson sampling
dc.subject.keywordmultinomial sampling
dc.subject.keywordproduct-multinomial sampling
dc.subject.keywordminimum phi-divergence estimator
dc.subject.keywordphi-divergence test statistics
dc.subject.keywordLoglinear models.
dc.subject.ucmEstadística matemática (Matemáticas)
dc.subject.unesco1209 Estadística
dc.titleNew families of estimators and test statistics in log-linear models
dc.typejournal article
dc.volume.number99
dcterms.referencesA. Agresti, An Introduction to Categorical Data Analysis, John Wiley & Sons, New York, 1996. MR1394195 (97c:62133) A. Agresti, Categorical Data Analysis, John Wiley & Sons, New York, 2002. R. Christensen, Log-Linear Model and Logistic Regression, Springer-Verlag, New York, 1997. N. Cressie, L. Pardo, Minimum φ-divergence estimator and hierarchical testing in loglinear models, Statistica Sinica 10 (2000) 867–884. N. Cressie, L. Pardo, Model checking in loglinear models using φ-divergences and MLEs, Journal of Statistical Planning and Inference 103 (2002) 437–453. N. Cressie, L. Pardo, M.C. Pardo, Size and power considerations for testing loglinear models using φ-divergence test statistics, Statistica Sinica 13 (2003) 555–570. N. Cressie, T.R.C. Read, Multinomial goodness-of-fit tests, Journal of the Royal Statistical Society Series B 46 (1984) 440–464. J.R. Dale, Asymptotic normality of goodness-of-fit statistics for sparse product multinomials, Journal of the Royal Statistical Society Series B 41 (1986) 48–59. MR0848050 (88f:62058) T.S. Ferguson, A Course in Large Sample Theory, Texts in Statistical Science, Chapman & Hall, London, 1996. A.K. Gupta, T. Nguyen, L. Pardo, Residual analysis and outliers in loglinear models based on phi-divergence statistics, Journal of Statistical Planning and Inference 137 (2007) 1407–1423. S.J. Haberman, The Analysis of Frequency Data, University of Chicago Press, Chicago, 1974. J.B. Lang, On the comparison of multinomial and Poisson log-linear models, Journal of the Royal Statistical Society Series B 58 (1996) 253–266. N. Martín, L. Pardo, Minimum Phi-divergence estimators for loglinear models with linear constraints and multinomial sampling, Statistical Papers 49 (2008) 15–36. I. Molina, D. Morales, Rényi statistics for testing hypotheses in mixed linear regression models, Journal of Statistical Planning and Inference 137 (2007) 87–102. L. Pardo, Statistical Inference based on Divergence Measures, in: Textbooks and Monographs, Chapman & Hall/CRC, New York, 2006. S.R. Searle, Linear Models, John Wiley & Sons, New York, 1971.
dspace.entity.typePublication
relation.isAuthorOfPublicationa6409cba-03ce-4c3b-af08-e673b7b2bf58
relation.isAuthorOfPublication.latestForDiscoverya6409cba-03ce-4c3b-af08-e673b7b2bf58

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