Weak Convergence of Serial Rank Statistics Under Dependence with Applications in Time Series and Markov Processes

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dc.contributor.authorPuri, Madan L.
dc.contributor.authorHarel, Michel
dc.date.accessioned2018-05-02T19:23:04Z
dc.date.available2018-05-02T19:23:04Z
dc.date.issued1990-07
dc.descriptionPublisher's, offprint versionen
dc.description.abstractThe asymptotic normality of linear serial rank statistics introduced by Hallin, Ingenbleek and Puri (1985) for the problem of testing white noise against ARMA alternatives is established for φ-mixing as well as strong mixing sequences of random variables. Applications in Markov processes and ARMA processes in time series are provided.en
dc.identifier.citationPuri, M. L. "Weak convergence of serial rank statistics under dependence with applications in time series and Markov processes." Annals of Probability (1990), Volume 18 Issue 3, 1361–1387. Co-author: Michel Harel.en
dc.identifier.urihttps://hdl.handle.net/2022/22057
dc.language.isoenen
dc.publisherThe Annals of Probabilityen
dc.relation.isversionofhttp://www.jstor.org/stable/2244429en
dc.subjectMarkov processesen
dc.subjectDistribution functionsen
dc.subjectTopological theoremsen
dc.subjectErgodic theoryen
dc.subjectStatistical theoriesen
dc.subjectPerceptron convergence procedureen
dc.subjectTrajectoriesen
dc.titleWeak Convergence of Serial Rank Statistics Under Dependence with Applications in Time Series and Markov Processesen
dc.typeArticleen

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