Please use this identifier to cite or link to this item: https://doi.org/10.1023/A:1022451015903
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dc.titleThe exact and limiting distributions for the number of successes in success runs within a sequence of Markov-dependent two-state trials
dc.contributor.authorFu, J.C.
dc.contributor.authorLou, W.Y.W.
dc.contributor.authorBai, Z.-D.
dc.contributor.authorLi, G.
dc.date.accessioned2014-10-28T05:15:52Z
dc.date.available2014-10-28T05:15:52Z
dc.date.issued2002
dc.identifier.citationFu, J.C., Lou, W.Y.W., Bai, Z.-D., Li, G. (2002). The exact and limiting distributions for the number of successes in success runs within a sequence of Markov-dependent two-state trials. Annals of the Institute of Statistical Mathematics 54 (4) : 719-730. ScholarBank@NUS Repository. https://doi.org/10.1023/A:1022451015903
dc.identifier.issn00203157
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/105419
dc.description.abstractThe total number of successes in success runs of length greater than or equal to k in a sequence of n two-state trials is a statistic that has been broadly used in statistics and probability. For Bernoulli trials with k equal to one, this statistic has been shown to have binomial and normal distributions as exact and limiting distributions, respectively. For the case of Markov-dependent two-state trials with k greater than one, its exact and limiting distributions have never been considered in the literature. In this article, the finite Markov chain imbedding technique and the invariance principle are used to obtain, in general, the exact and limiting distributions of this statistic under Markov dependence, respectively. Numerical examples are given to illustrate the theoretical results.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1023/A:1022451015903
dc.sourceScopus
dc.subjectFinite Markov chain imbedding
dc.subjectRuns and patterns
dc.subjectTransition probability matrix
dc.typeArticle
dc.contributor.departmentSTATISTICS & APPLIED PROBABILITY
dc.description.doi10.1023/A:1022451015903
dc.description.sourcetitleAnnals of the Institute of Statistical Mathematics
dc.description.volume54
dc.description.issue4
dc.description.page719-730
dc.description.codenAISXA
dc.identifier.isiut000180553700002
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