Aviso: para depositar documentos, por favor, inicia sesión e identifícate con tu cuenta de correo institucional de la UCM con el botón MI CUENTA UCM. No emplees la opción AUTENTICACIÓN CON CONTRASEÑA
 

Testing equality restrictions in generalized linear models for multinomial data

dc.contributor.authorPardo Llorente, María del Carmen
dc.date.accessioned2023-06-20T00:21:25Z
dc.date.available2023-06-20T00:21:25Z
dc.date.issued2011-03
dc.descriptionThe author would like to thank a referee for critically reading this paper and making suggestions. This work was partially supported by Grants MTM2006-06872 and BSCH-UCM2008-910707.
dc.description.abstractBased on φ-divergences an estimator of the generalized linear models for multinomial data under linear restrictions on the parameters is considered. New test statistics, also based on φ-divergences are considered as alternatives to the classical ones for testing a hypothesis about linear restrictions on the parameters. The asymptotic distribution of them is obtained under the null hypothesis as well as under contiguous local hypotheses. An application of the estimators and the tests is illustrated in a numerical example and in simulation studies. contiguous local hypotheses.An application of the estimators and the tests is illustrated in a numerical example and in simulation studies.
dc.description.departmentDepto. de Estadística e Investigación Operativa
dc.description.facultyFac. de Ciencias Matemáticas
dc.description.refereedTRUE
dc.description.sponsorshipGrants
dc.description.sponsorshipBSCH-UCM
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/17458
dc.identifier.doi10.1007/s00184-009-0275-y
dc.identifier.issn0026-1335
dc.identifier.officialurlhttp://link.springer.com/article/10.1007%2Fs00184-009-0275-y
dc.identifier.relatedurlhttp://www.springer.com/?SGWID=5-102-0-0-0
dc.identifier.urihttps://hdl.handle.net/20.500.14352/42448
dc.issue.number2
dc.journal.titleMetrika
dc.language.isoeng
dc.page.final253
dc.page.initial231
dc.publisherSpringer Heidelberg
dc.relation.projectIDMTM2006-06872
dc.relation.projectID2008-910707
dc.rights.accessRightsrestricted access
dc.subject.cdu519.22
dc.subject.keywordGeneralized linear models for multinomial data
dc.subject.keywordRestricted minimum φ-divergence estimation
dc.subject.keywordLinear restrictions
dc.subject.keywordφ-divergence test statistics
dc.subject.ucmEstadística matemática (Matemáticas)
dc.subject.unesco1209 Estadística
dc.titleTesting equality restrictions in generalized linear models for multinomial data
dc.typejournal article
dc.volume.number73
dcterms.referencesAgresti A (2002) Categorical data analysis, 2nd edn. Wiley, New York Ali SM, Silvey SD (1966) A general class of coefficients of divergence of one distribution from another. J R Stat Soc Ser B 26: 131–142 Cressie NAC, Read T (1984) Multinomial goodness-of-fit tests. J R Stat Soc B 46: 440–464 Fahrmeir L, Tutz G (2001) Multivariate statistical modelling based on generalized linear models. Springer, New York Ferguson TS (1996) A course in large sample theory. Wiley, New York Finney DJ (1971) Probit analysis, 3rd edn. Cambridge University Press, London Flemming W (1977) Functions of several variables, 2nd edn. Springer, New York Grewal RS (1952) A method for testing analgesics in mice. Br J Pharm Chemother 7: 433–437 Le Cam L (1960) Locally asymptotic normal families of distribution. University of California Publications in Statistics, Berkeley Liu I, Agresti A (2005) The analysis of ordered categorical data: an overview and a survey of recent developments. Test 14(1): 1–73 Nelder JA, Wedderburn RWM (1972) Generalized linear models. J R Stat Soc A135: 370–384 Nyquist H (1991) Restricted estimation of generalized linear models. J Appl Stat 40(1): 133–141 Pardo L (2006) Statistical inference based on divergence measures. Chapman & Hall, London Pardo MC (2007) ϕ -divergence estimation in GLM for ordinal responses. Technical Report, no 67. Complutense University of Madrid Rivas MJ, Santos MT, Morales D (1995) Ré nyi test statistics for partially observed diffusion processes. J Stat Plan Inference 127: 91–102 Vajda I (1989) Theory of statistical inference and information. Kluwer Academic Publishers, Dordrecht
dspace.entity.typePublication

Download

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
PardoCarmen02.pdf
Size:
327.68 KB
Format:
Adobe Portable Document Format

Collections