Phi-divergences and polytomous logistic regression models: An overview
dc.contributor.author | Gupta, Arjun K. | |
dc.contributor.author | Pardo Llorente, Leandro | |
dc.date.accessioned | 2023-06-20T09:44:07Z | |
dc.date.available | 2023-06-20T09:44:07Z | |
dc.date.issued | 2007-11-01 | |
dc.description | Special Issue: In Celebration of the Centennial of The Birth of Samarendra Nath Roy (1906-1964) | |
dc.description.abstract | In this paper we assume that the categorical data are distributed according to a multinomial distribution whose probabilities follow a polytomous logistic regression model and we present some inferential results based on minimum phi-divergence estimators as well as phi-divergence test statistics. | |
dc.description.department | Depto. de Estadística e Investigación Operativa | |
dc.description.faculty | Fac. de Ciencias Matemáticas | |
dc.description.refereed | TRUE | |
dc.description.sponsorship | DGI | |
dc.description.sponsorship | UCM | |
dc.description.status | pub | |
dc.eprint.id | https://eprints.ucm.es/id/eprint/17619 | |
dc.identifier.doi | 10.1016/j.jspi.2007.03.028 | |
dc.identifier.issn | 0378-3758 | |
dc.identifier.officialurl | http://www.sciencedirect.com/science/article/pii/S0378375807001139 | |
dc.identifier.relatedurl | http://www.sciencedirect.com/ | |
dc.identifier.uri | https://hdl.handle.net/20.500.14352/50270 | |
dc.issue.number | 11 | |
dc.journal.title | Journal of statistical planning and inference | |
dc.language.iso | eng | |
dc.page.final | 3524 | |
dc.page.initial | 3513 | |
dc.publisher | Elsevier Science BV. | |
dc.relation.projectID | MTM2006-06872 | |
dc.relation.projectID | UCM2006-910707 | |
dc.rights.accessRights | restricted access | |
dc.subject.cdu | 519.2 | |
dc.subject.keyword | multinomial sampling | |
dc.subject.keyword | dimensionality reduction | |
dc.subject.keyword | kullback-leibler divergence | |
dc.subject.keyword | phi-divergence test statistic | |
dc.subject.ucm | Estadística matemática (Matemáticas) | |
dc.subject.unesco | 1209 Estadística | |
dc.title | Phi-divergences and polytomous logistic regression models: An overview | |
dc.type | journal article | |
dc.volume.number | 137 | |
dcterms.references | Andersen, E.B., 1994. The Statistical Analysis of Categorical Data. Springer, NewYork. Cressie, N., Pardo, L., Pardo, M.C., 2003. Size and power considerations for testing loglinear models using phi-divergence test statistics. Statist. Sinica 13, 550–570. Gupta, A.K., Kasturiratna, D., Nguyen, T., Pardo, L., 2006a. Anewfamily of BANestimators in politomous regression models based on phi-divergence measures. Statist. Meth. Appl. 15 (2), 159–176. Gupta, A.K., Nguyen, T., Pardo, L., 2006b. Some inference procedures in polytomous logistic regression models based on phi-divergences measures. Math. Methods Statist. 15 (3), 269–288. Gupta, A.K., Nguyen, T., Pardo, L., 2007. Residual for polytomous logistic regression models based on phi-divergences test statistics. Statistics, in press. Lesaffre, E., Albert, A., 1989. Multiple-group logistic regression diagnostic. Appl. Statist. 38, 425–440. Liu, A., Agresti, A., 2005. The analysis of categorical data: an overview and a survey of recent developments. Test 14 (1), 1–74. Pardo, J.A., Pardo, L., Zografos, K., 2002. Minimum phi-divergence estimator with constraints in multinomial populations. J. Statist. Plann. Inference 104, 221–237. Pardo, J.A., Pardo, L., Pardo, M.C., 2005. Minimum phi-divergence estimator in logistic regression model. Statist. Papers 47, 91–108. Pardo, J.A., Pardo, L., Pardo, M.C., 2006. Testing in logistic regression models based on phi-divergence measures. J. Statist. Plann. Inference 136, 982–1006. Pardo, L., 2006. Statistical Inference Based on Divergence Measures. Statistics: Textbooks and Monographs. Chapman & Hall, CRC, NewYork. | |
dspace.entity.type | Publication | |
relation.isAuthorOfPublication | a6409cba-03ce-4c3b-af08-e673b7b2bf58 | |
relation.isAuthorOfPublication.latestForDiscovery | a6409cba-03ce-4c3b-af08-e673b7b2bf58 |
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