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Large deviations for Markov chains /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Large deviations for Markov chains // Alejandro D. de Acosta, Case Western Reserve University.
作者:	Acosta, Alejandro D. de,
面頁冊數:	1 online resource (xii, 249 pages) :digital, PDF file(s). :
附註:	Title from publisher's bibliographic system (viewed on 19 Aug 2022).
標題:	Markov processes. -
電子資源:	https://doi.org/10.1017/9781009053129
ISBN:	9781009053129 (ebook)

Large deviations for Markov chains /
Acosta, Alejandro D. de,1941-

Large deviations for Markov chains /Alejandro D. de Acosta, Case Western Reserve University. - 1 online resource (xii, 249 pages) :digital, PDF file(s). - Cambridge tracts in mathematics ;229. - Cambridge tracts in mathematics ;203..

Title from publisher's bibliographic system (viewed on 19 Aug 2022).

This book studies the large deviations for empirical measures and vector-valued additive functionals of Markov chains with general state space. Under suitable recurrence conditions, the ergodic theorem for additive functionals of a Markov chain asserts the almost sure convergence of the averages of a real or vector-valued function of the chain to the mean of the function with respect to the invariant distribution. In the case of empirical measures, the ergodic theorem states the almost sure convergence in a suitable sense to the invariant distribution. The large deviation theorems provide precise asymptotic estimates at logarithmic level of the probabilities of deviating from the preponderant behavior asserted by the ergodic theorems.

ISBN: 9781009053129 (ebook)Subjects--Topical Terms:

527825
Markov processes.

LC Class. No.: QA273.67 / .A265 2022

Dewey Class. No.: 519.2/33

Large deviations for Markov chains /
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500 $a Title from publisher's bibliographic system (viewed on 19 Aug 2022).
520 $a This book studies the large deviations for empirical measures and vector-valued additive functionals of Markov chains with general state space. Under suitable recurrence conditions, the ergodic theorem for additive functionals of a Markov chain asserts the almost sure convergence of the averages of a real or vector-valued function of the chain to the mean of the function with respect to the invariant distribution. In the case of empirical measures, the ergodic theorem states the almost sure convergence in a suitable sense to the invariant distribution. The large deviation theorems provide precise asymptotic estimates at logarithmic level of the probabilities of deviating from the preponderant behavior asserted by the ergodic theorems.
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650 0 $a Large deviations. $3 527871
776 0 8 $i Print version: $z 9781316511893
830 0 $a Cambridge tracts in mathematics ; $v 203. $3 1238301
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