Asymptotic Optimality of Mixture Rules for Detecting Changes in General Stochastic Models
Asymptotic Optimality of Mixture Rules for Detecting Changes in General Stochastic Models
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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The paper addresses a sequential changepoint detection problem for a general stochastic model, assuming that the observed data may be non-i.i.d. (i.e., dependent and non-identically distributed) and the prior distribution of the change point is arbitrary. Tartakovsky and Veeravalli (2005), Baron and Tartakovsky (2006), and, more recently, Tartakovs...
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Asymptotic Optimality of Mixture Rules for Detecting Changes in General Stochastic Models
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TN_cdi_proquest_journals_2092809878
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2092809878
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2331-8422
