An approach to multiway contingency tables based on phi-divergence test statistics
| dc.contributor.author | Pardo Llorente, Julio Ángel | |
| dc.date.accessioned | 2023-06-20T00:22:21Z | |
| dc.date.available | 2023-06-20T00:22:21Z | |
| dc.date.issued | 2010-11 | |
| dc.description.abstract | In this paper, we consider independence models for three-dimensional tables under multinomial sampling. We use the restricted minimum phi-divergence estimator in a phi-divergence statistic, which is the basis of some new test statistics, for solving the classical problem of testing independence in three-dimensional contingency tables. | |
| 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/17647 | |
| dc.identifier.doi | 10.1016/j.jmva.2010.06.003 | |
| dc.identifier.issn | 0047-259X | |
| dc.identifier.officialurl | http://www.sciencedirect.com/science/article/pii/S0047259X10001223# | |
| dc.identifier.relatedurl | http://www.sciencedirect.com | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14352/42471 | |
| dc.issue.number | 10 | |
| dc.journal.title | Journal of multivariate analysis | |
| dc.language.iso | eng | |
| dc.page.final | 2319 | |
| dc.page.initial | 2305 | |
| dc.publisher | Elsevier | |
| dc.relation.projectID | MTM2009-06997 | |
| dc.relation.projectID | BSCH-UCM-2008-910707(GR58/08) | |
| dc.rights.accessRights | restricted access | |
| dc.subject.cdu | 519.237 | |
| dc.subject.keyword | Three-dimensional contingency table | |
| dc.subject.keyword | phi-divergence measure | |
| dc.subject.keyword | Independence | |
| dc.subject.ucm | Estadística matemática (Matemáticas) | |
| dc.subject.unesco | 1209 Estadística | |
| dc.title | An approach to multiway contingency tables based on phi-divergence test statistics | |
| dc.type | journal article | |
| dc.volume.number | 101 | |
| dcterms.references | A. Agresti, Categorical Data Analysis, John Wiley, 1990. S.M. Ali, S.D. Silvey, A general class of coefficients of divergence of one distribution from another, Journal of the Royal Statistical Society, Series B 26 (1966) 131-142. E.B. Andersen, Introduction to the Statistical Analysis of Categorical Data, Springer-Verlag, 1998. M.S. Bartlett, Contingency table interactions, Supplement to the Journal of the Royal Statistical Society 2 (2) (1935) 248-252. E.J. Beh, B. Simonetti, L. D'Ambra, Partitioning a non-symmetric measure of association for three way contingency tables, Journal of Multivariate Analysis 98 (7) (2007) 1391-1411. V.P. Bhapkar, G.G. Koch, Hypothesis of `no interaction' in multidimensional contingency tables, Technometrics 10 (1968) 107-123. A. Bhattacharyya, On a measure of divergence between two statistical populations defined by their probability distribution, Bulletin of the Calcutta Mathematical Society 35 (1946) 99-104. M.W. Birch, A new proof of the Pearson-Fisher theorem, Annals of Mathematical Statistics 35 (1964) 817-824. R. Christensen, Log-Linear Models and Logistic Regression, Springer-Verlag, 1997. N. Cressie, T.R.C. Read, Multinomial goodness-of-fit tests, Journal of the Royal Statistical Society, Series B 46 (1984) 440-464. I. Csiszár, Eine informationstheoretische Ungleichung und ihre Anwendung auf den Beweis der Ergodizität on Markhoffschen Ketten, Publications of the Mathematical Institute of Hungarian Academy of Sciences, Series A 8 (1963) 85-108. 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. E.L. Diamond, S.K. Mitra, S.N. Roy, Asymptotic power and asymptotic independence in the statistical analysis of categorical data, Bulletin de l'Institud International de Statistique 37 (3) (1960) 309-329. B.S. Everitt, The Analysis of Contingency Tables, Chapman & Hall, 2001. D.H. Freeman, Applied Categorical Data Analysis, Marcel Dekker, 1987. D.V. Gokhale, S. Kullback, Iterative maximum likelihood estimation for discrete distributions, Sankhya 35 (1978) 293-298. Z. Gilula, J. Haberman, Canonical analysis of contingency tables by maximum likelihood, Journal of the American Statistical Association 81 (1986) 780-788. 395. N.S. Johnson, C� method for testing significance in the rxc contingency table, Journal of the American Statistical Association 70 (352) (1975) 942-947. M.L. Menéndez, J.A. Pardo, L. Pardo, Tests based on phi-divergences for bivariate symmetry, Metrika 53 (2001) 15-29. | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | 5e051d08-2974-4236-9c25-5e14369a7b61 | |
| relation.isAuthorOfPublication.latestForDiscovery | 5e051d08-2974-4236-9c25-5e14369a7b61 |
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