Aviso: para depositar documentos, por favor, inicia sesión e identifícate con tu cuenta de correo institucional de la UCM con el botón MI CUENTA UCM. No emplees la opción AUTENTICACIÓN CON CONTRASEÑA
 

Csiszar's phi-divergences for testing the order in a Markov chain

dc.contributor.authorMenéndez Calleja, María Luisa
dc.contributor.authorPardo Llorente, Julio Ángel
dc.contributor.authorPardo Llorente, Leandro
dc.date.accessioned2023-06-20T17:06:28Z
dc.date.available2023-06-20T17:06:28Z
dc.date.issued2001-07
dc.description.abstractAssume that a sequence of observations x(1),...,x(n+r) can be treated as the sample values of a Markov chain of order r or less (chain in which the dependence extends over r+1 consecutive variables only), and consider the problem of testing the hypothesis No that a chain of order r - 1 will be sufficient on the basis of the tools given by the Statistical Information Theory: rho -Divergences. More precisely, if p(a1),...,(ar:ar+1) denotes the transition probability for a r(th) order Markov chain, the hypothesis to be tested is H-0 : p(a1),...,(ar:ar+1) = p(a2),...,(ar):(ar+1), a(i) is an element of {1,...,s}, i = 1,..., r + 1 The tests given in this paper, for the first time, will have as a particular case the likelihood ratio test and the test based on the chi-squared statistic.
dc.description.departmentDepto. de Estadística e Investigación Operativa
dc.description.facultyFac. de Ciencias Matemáticas
dc.description.refereedTRUE
dc.description.sponsorshipDGES
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/17554
dc.identifier.doihttp://dx.doi.or/10.1007/s003620100061
dc.identifier.issn0932-5026
dc.identifier.officialurlhttp://www.springerlink.com/content/wtr4a6q9bqftaq6w/fulltext.pdf
dc.identifier.relatedurlhttp://www.springerlink.com
dc.identifier.urihttps://hdl.handle.net/20.500.14352/57781
dc.issue.number3
dc.journal.titleStatistical Papers
dc.language.isoeng
dc.page.final328
dc.page.initial313
dc.publisherSpringer Verlag
dc.relation.projectIDPB96-0635
dc.rights.accessRightsrestricted access
dc.subject.cdu519.216
dc.subject.keywordr th Markov chains
dc.subject.keywordCsiszar's phi-divergences
dc.subject.keywordStatistical Information Theory
dc.subject.keywordgoodness of fit tests
dc.subject.keyworddivergence statistics.
dc.subject.ucmProbabilidades (Matemáticas)
dc.titleCsiszar's phi-divergences for testing the order in a Markov chain
dc.typejournal article
dc.volume.number42
dcterms.referencesAli, S. M. and S. D. Silvey (1966). A general class of coefficient of divergence of one distribution from another. J. of Royal Statistical Society, Ser. B, 286, 131-142. Anderson, T.W. and Goodman, L.A. (1957). Statistical inference about Markov chains. Ann. Math. Star., 28, 89-110 Azlarov, T.A. and A. A. Narkhuzhaev (1987). Asymptotic analysis of some chi-square type tests for Markov chains. Dokl. Akad. Nauk. SSSR, 7, 3-5. Azlarov, T.A. and A. A. Narkhuzhaev (1992). On asymptotic behavior of distributions of some statistics for Markov chains. Theory Probab. Appl., 37, 117-119. Basawa, I.V. and B.L.S. Prakasa Rao (1980). Statistical Inference for Stochastic Processes. Academic Press, London. Billingsley, P. (1961a). Statistical methods in Markov chains. Ann. Math. Statist., 32, 13-39. Billingsley, P. (1961b). Statistical Inference for Markoy Processes. The University of Chicago Press. Csiszar, I. (1963). Eine informationstheoretische Ungleichung und ihre Anwendung auf den Beweis der Ergodizität von Markoffschen Ketten. Publications of the Mathematical Institute of Hungarian Academy of Sciences, Ser. A, 8, 85-108. Cressie, N. and Read, T. R. C. (1984). Multinomial goodness of fit tests. J. of Royal Statistical Society, Ser. B, 46,440-464. Cox, C. (1984). An elementary introduction to maximum likelihood estimation for multinomial models: Birh's theorem and the delta method. The American Statistician, 38, 283-287. Ferguson, T.S. (1996). A Course in Large Sample Theory. Chapman and Hall. Fraser, D.A.S. (1957). Nonparametric Methods in Statistics. Wiley, New York. Hoel, P. G. (1954). A test for Markov chains. Biometrika, 14, 430-433. Ivchenko, G. and Y. Medvedev (1990). Mathematical Statistics. Mir, MOSCOW. Menéndez, M.L., Morales, D., Pardo, L. and Zografos, K. (1999). Statistical inference for finite Markov chains based on Divergences. Statistics and Probability Letters, 41, 9-17. Mirvaliev, M. and A.A. Narkhuzhaev (1990). On a chi-square test for homogeneous Markov chains. Izv. Akad. Nauk. Uzb. SSR, Ser. Fiz.-Mat., 1, 28-32. Morales, D.; Pardo, L. and I. Vajda (1995). Asymptotic divergence of estimates of discrete distributions. J. of Statistical Planning and Inference, 48, 347-369. Read, T.R.C. and N.A.C. Cressie (1988). Goodness-of-fit Statistics for Discrete Multivariate Data. Springer, Berlin. Roussas, G.G. (1979). Asymptotic distribution of the log-likelihood function for stochastic processes. Z. Wahr. Verw. Geb., 47, 31-46. Salicrfi, M., Morales, D., Menéndez, M.L. and Pardo, L. (1994). On the applications of divergence type measures in testing statistical hypotheses. J. of Multivariate Analysis, 51, 372-391. Zografos, K., Ferentinos, K. and T. Papaioannou (1990). phi-divergence statistics: sampling properties and multinomial goodness of fit and divergence tests". Commun.Statist. (Theory and Meth.), 19(5), 1785-1802.
dspace.entity.typePublication
relation.isAuthorOfPublication5e051d08-2974-4236-9c25-5e14369a7b61
relation.isAuthorOfPublicationa6409cba-03ce-4c3b-af08-e673b7b2bf58
relation.isAuthorOfPublication.latestForDiscovery5e051d08-2974-4236-9c25-5e14369a7b61

Download

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
PardoJulio28.pdf
Size:
2.33 MB
Format:
Adobe Portable Document Format

Collections