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Hypothesis testing for two discrete populations based on the Hellinger distance

dc.contributor.authorBasu, Ayanendranath
dc.contributor.authorMandal, Abhijit
dc.contributor.authorPardo Llorente, Leandro
dc.date.accessioned2023-06-20T00:20:33Z
dc.date.available2023-06-20T00:20:33Z
dc.date.issued2010-02-01
dc.description.abstractOur interest is in the problem where independent samples are drawn from two different discrete populations, possibly with a common parameter. The goal is to test hypothesis about the parameters involved in these two samples. A number of tests are developed for the above purpose based on the Hellinger distance and penalized versions of it. The asymptotic distributions of the test statistics are derived. Extensive simulation results are provided, which illustrate the theory developed and the robustness of the methods.
dc.description.departmentDepto. de Estadística e Investigación Operativa
dc.description.facultyFac. de Ciencias Matemáticas
dc.description.refereedTRUE
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/17349
dc.identifier.doi10.1016/j.spl.2009.10.008
dc.identifier.issn0167-7152
dc.identifier.officialurlhttp://www.sciencedirect.com/science/article/pii/S0167715209003940
dc.identifier.relatedurlhttp://www.sciencedirect.com/
dc.identifier.urihttps://hdl.handle.net/20.500.14352/42425
dc.issue.number3-4
dc.journal.titleStatistics and probability letters
dc.language.isoeng
dc.page.final214
dc.page.initial202
dc.publisherElsevier Science Bv.
dc.relation.projectIDMTM2009-10072
dc.rights.accessRightsrestricted access
dc.subject.cdu519.217
dc.subject.keywordModels
dc.subject.keywordEfficiency
dc.subject.ucmEstadística matemática (Matemáticas)
dc.subject.unesco1209 Estadística
dc.titleHypothesis testing for two discrete populations based on the Hellinger distance
dc.typejournal article
dc.volume.number80
dcterms.referencesBasu and Basu, 1998 A. Basu, S. Basu, Penalized minimum disparity methods for multinomial models, Statistica Sinica, 8 (1998), pp. 841–860 Basu et al., 1996 A. Basu, I.R. Harris, S. Basu, Tests of hypothesis in discrete models based on the penalized Hellinger distance, Statistics & Probability Letters, 27 (1996), pp. 367–373 Basu et al., 1997, A. Basu, I.R. Harris, S. Basu, Minimum distance estimation: The approach using density based distances, in: G.S. Maddala, C.R. Rao (Eds.), Robust Inference, Handbook of Statistics, vol. 15, Elsevier Science, New York, NY (1997), pp. 21–48 Beran, 1977 , R. Beran, Minimum Hellinger distance estimates for parametric models, Annals of Statistics, 5 (1977), pp. 445–463 Bishop et al., 1975, M.M. Bishop, S.E. Fienberg, P.W. Holland, Discrete Multivariate Analysis: Theory and Practice, MIT Press, Cambridge, Mass (1975) Harris and Basu, 1994, I.R. Harris, A. Basu, Hellinger distance as a penalized log likelihood, Communications in Statistics. Simulation and Computation, 23 (1994), pp. 1097–1113 Kullback, 1985, S. Kullback, Kullback information, S. Kotz, Johnson (Eds.), Encyclopedia of Statistical Sciences, vol. 4John Wiley & Sons, New York (1985), pp. 421–425 Kupperman, 1957, Kupperman, M., 1957. Further application to information theory to multivariate analysis and statistical inference. Ph.D. Dissertation, George Washington University Lindsay, 1994 , B.G. Lindsay, Efficiency versus robustness: The case for minimum Hellinger distance and related methods, Annals of Statistics, 22 (1994), pp. 1081–1114 Mandal et al., 2008, Mandal, A., Basu, A., Pardo, L., 2008. Minimum Hellinger distance inference and the empty cell penalty: Asymptotic results. Technical Report No. ASD/2008/3, Indian Statistical Institute Pardo, 2006, L. Pardo, Statistical Inference Based on Divergence Measures, Chapman & Hall/CRC (2006) Salicrú et al., 1994, M. Salicrú, D. Morales, M.L. Menéndez, L. Pardo, On the applications of divergence type measures in testing statistical hypotheses, Journal of Multivariate Analysis, 51 (1994), pp. 372–391. Sarkar and Basu, 1995, S. Sarkar, A. Basu, On disparity based robust tests for two discrete populations, Sankhya B, 57 (1995), pp. 353–364. Sen and Singer, 1993, P.K. Sen, J.M. Singer, Large Sample Methods in Statistics, Chapman & Hall (1993). Serfling, 1980, R. Serfling, Approximation Theorems of Mathematical Statistics, Wiley, New York (1980) Simpson, 1987, D.G. Simpson, Minimum Hellinger distance estimation for analysis of count data, Journal of the American Statistical Association, 82 (1987), pp. 802–807 Simpson, 1989, D.G. Simpson, Hellinger deviance tests: Efficiency, breakdown points and examples, Journal of the American Statistical Association, 84 (1989), pp. 107–113
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relation.isAuthorOfPublication.latestForDiscoverya6409cba-03ce-4c3b-af08-e673b7b2bf58

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