Testing in logistic regression models based on phi-divergences measures
| dc.contributor.author | Pardo Llorente, Julio Ángel | |
| dc.contributor.author | Pardo Llorente, Leandro | |
| dc.contributor.author | Pardo Llorente, María del Carmen | |
| dc.date.accessioned | 2023-06-20T09:42:59Z | |
| dc.date.available | 2023-06-20T09:42:59Z | |
| dc.date.issued | 2006 | |
| dc.description.abstract | In this paper, we consider inference based on very general divergence measures under assumptions of a logistic regression model. We use the minimum phi-divergence estimator in a phi-divergence statistic, which is the basis of some new statistics, for solving the classical problems of testing in a logistic regression model. A diagnostic analysis is developed based on the new estimators and test statistics. | |
| dc.description.department | Depto. de Estadística e Investigación Operativa | |
| dc.description.faculty | Fac. de Ciencias Matemáticas | |
| dc.description.refereed | TRUE | |
| dc.description.status | pub | |
| dc.eprint.id | https://eprints.ucm.es/id/eprint/17476 | |
| dc.identifier.doi | 10.1016/j.jspi.2004.08.008 | |
| dc.identifier.issn | 0378-3758 | |
| dc.identifier.officialurl | http://www.sciencedirect.com/science/article/pii/S0378375804003441 | |
| dc.identifier.relatedurl | http://www.sciencedirect.com | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14352/50237 | |
| dc.issue.number | 3 | |
| dc.journal.title | Journal of Statistical Planning and Inference | |
| dc.language.iso | eng | |
| dc.page.final | 1006 | |
| dc.page.initial | 982 | |
| dc.publisher | Elsevier Science | |
| dc.relation.projectID | DGI (BMF2003-00892) | |
| dc.rights.accessRights | restricted access | |
| dc.subject.cdu | 519.22 | |
| dc.subject.keyword | Logistic regression model | |
| dc.subject.keyword | phi-divergence measure | |
| dc.subject.keyword | Goodness-of-fit tests | |
| dc.subject.keyword | Model diagnostics | |
| dc.subject.ucm | Estadística matemática (Matemáticas) | |
| dc.subject.unesco | 1209 Estadística | |
| dc.title | Testing in logistic regression models based on phi-divergences measures | |
| dc.type | journal article | |
| dc.volume.number | 136 | |
| dcterms.references | Agresti, A., 1996. An Introduction to Categorical Data Analysis,Wiley, NewYork. Ali, S.M., Silvey, S.D., 1966.A general class of coefficients of divergence of one distribution from another. J. Roy. Statist. Soc. Ser. B 28, 131–142. Belsley, D.A., Kuh, E., Welsch, R.E., 1980. Regression Diagnostics: Identifying Influential Data and Sources of Collinearity,Wiley, NewYork. Brown, C.C., 1982. On a goodness-of-fit test for logistic model based on score statistics. Commun. Statist. 11,1087–1105. Cook, R.D., 1977. Detection of influential observations in linear regression. Technometrics 19, 15–18. Cook, R.D.,Weisberg, S., 1982. Residuals and Influence in Regression, Chapman and Hall, NewYork. Cox, D.R., Snell, E.J., 1989. Analysis of Binary Data, Chapman and Hall, NewYork. Cressie, N., Read, T.R.C., 1984. Multinomial goodness-of- it tests. J. Roy. Statist. Soc. Ser. B 46, 440–464. Csiszár, I., 1963. Eine Informationtheorestiche Ungleichung und ihre Anwendung anf den Beweis der Ergodizität Markoffshen Ketten. Publ. Math. Inst. Hungarian Acad. Sci. Ser. A 8, 84–108. Dale, J.R., 1986. Asymptotic normality of goodness-of-fit statistics for sparse product multinomials. J. Roy. Statist. Soc. Ser. B 41, 48–59. Jennings, D.E., 1986. Judging inference adequacy in Logistic regression. J. Amer. Statist. Assoc. 81 (396),987–990. Kleinbaum, D.G.,Kupper, L.L., Muller, K.E., 1987. Applied RegressionAnalysis and other Multivariable Methods, PWS-Kent, Boston. Kullback, S., 1985. Kullback information. In: Kotz, S., Johnson, N.L. (Eds.), Encyclopedia of Statistical Sciences, Vol. 4.Wiley, NewYork, pp. 421–425. | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | 5e051d08-2974-4236-9c25-5e14369a7b61 | |
| relation.isAuthorOfPublication | a6409cba-03ce-4c3b-af08-e673b7b2bf58 | |
| relation.isAuthorOfPublication.latestForDiscovery | 5e051d08-2974-4236-9c25-5e14369a7b61 |
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