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Goodness-of-fit tests for stationary distributions of Markov chains based on Rao's divergence

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dc.contributor.authorPardo Llorente, María del Carmen
dc.date.accessioned2023-06-20T17:08:20Z
dc.date.available2023-06-20T17:08:20Z
dc.date.issued1998-03
dc.descriptionThis work was supported by grant DGICYT PB96-0635
dc.description.abstractGoodness-of-fit tests based on Rao's divergence between observed and theoretical frequencies for stationary distributions of Markov chains are considered. The asymptotic distribution of these tests under uniform hypothesis is obtained. A power comparison of the proposed tests is carried out in the case of binary Markov data.
dc.description.departmentDepto. de Estadística e Investigación Operativa
dc.description.facultyFac. de Ciencias Matemáticas
dc.description.refereedTRUE
dc.description.sponsorshipDGICYT
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/17836
dc.identifier.doi10.1016/S0020-0255(97)10028-7
dc.identifier.issn0020-0255
dc.identifier.officialurlhttp://www.sciencedirect.com/science/article/pii/S0020025597100287
dc.identifier.relatedurlhttp://www.sciencedirect.com/
dc.identifier.urihttps://hdl.handle.net/20.500.14352/57829
dc.issue.number1-4
dc.journal.titleInformation Sciences
dc.language.isoeng
dc.page.final122
dc.page.initial115
dc.publisherElsevier Science Inc
dc.relation.projectIDPB96-0635
dc.rights.accessRightsrestricted access
dc.subject.cdu519.216
dc.subject.keywordGoodness-of-fit tests
dc.subject.keywordMarkov chain
dc.subject.keywordRao's divergence
dc.subject.keywordMost powerful test
dc.subject.ucmProcesos estocásticos
dc.subject.unesco1208.08 Procesos Estocásticos
dc.titleGoodness-of-fit tests for stationary distributions of Markov chains based on Rao's divergence
dc.typejournal article
dc.volume.number105
dcterms.referencesS. Tavaré, P.M.E. Altham, Serial dependence of observations leading to contingency tables,and corrections to chi-squared statistics. Biometrika, 70 (1983), pp. 139–144 M.L. Menéndez, D. Morales, L. Pardo, I. Vajda, Testing in stationary models based on f-divergences of observed and theoretical frequencies. Kybernetika, 33 (1997), pp. 465–475 I. Csiszár, Eine Informationtheoretische Ungleichung und ihre Anwendung auf den Bewis der Ergodizität von Markhoffschen Ketten. Publ. Math. Inst. Hungar. Acad. Sci. Ser. A, 8 (1963), pp. 85–108 J. Burbea, C.R. Rao, On the convexity of some divergence measures based on Entropy functions. IEEE Trans. Inf. Theory, 28 (1982), pp. 489–495 M.C. Pardo, On Burbea-Rao divergences based goodness-of-fit tests for multinomial models (submitted). M.C. Pardo, Goodness-of-fit tests based on Rao's divergence under sparseness assumptions (submitted). M.C. Pardo, I. Vajda, About distances of discrete distributions satisfying the Data Processing Theorem of Information Theory. IEEE Trans. Inf. Theory, 43 (4) (1997), pp. 1288–1293 A. Cohen, H.B. Sakrowitz, Unbiasedness of the chi-square, likelihood ratio, and other goodness of fit tests for the equal cell case. Ann. Statist., 3 (1975), pp. 959–964 T. Bednarski, T. Ledwina, A note on a biasedness of tests of fit. Mathematische Operationsforschung und Statistik, Series Statistics, 9 (1978), pp. 191–193 P. Billingsley, Statistical methods in Markov chains, Ann. Math. Statist., 32 (1961), pp. 12–40
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