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Titlebook: Markov Chains with Stationary Transition Probabilities; Kai Lai Chung Textbook 1960 Springer-Verlag Berlin Heidelberg 1960 Markov chain.Ma

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11#
發(fā)表于 2025-3-23 11:19:39 | 只看該作者
12#
發(fā)表于 2025-3-23 14:33:46 | 只看該作者
The moments of first entrance time distributionsIf . =1, then the sequence {., .≧1} determines a discrete probability distribution called the .. (For . = . this has also already been called the recurrence time distribution of . in §6.) Thus for each ., . is the moment of order . of this distribution; for .=. this is the . defined in § 9. More generally, let . be the taboo set; we write
13#
發(fā)表于 2025-3-23 20:21:18 | 只看該作者
14#
發(fā)表于 2025-3-24 01:08:35 | 只看該作者
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發(fā)表于 2025-3-24 05:56:53 | 只看該作者
16#
發(fā)表于 2025-3-24 06:43:37 | 只看該作者
Further limit theoremsIn this section we give several more limit theorems about . including the central limit theorem and the law of the iterated logarithm. The state space . will now be assumed to be positive class, in fact except in Theorem 1 below the stronger assumption that .< ∞ for some and hence all . will be made.
17#
發(fā)表于 2025-3-24 14:11:54 | 只看該作者
978-3-642-49408-6Springer-Verlag Berlin Heidelberg 1960
18#
發(fā)表于 2025-3-24 16:20:52 | 只看該作者
Markov Chains with Stationary Transition Probabilities978-3-642-49686-8Series ISSN 0072-7830 Series E-ISSN 2196-9701
19#
發(fā)表于 2025-3-24 22:55:02 | 只看該作者
20#
發(fā)表于 2025-3-24 23:57:26 | 只看該作者
Fundamental defintionson probabilities” so that the qualifying phrase in quotes will be understood. Finally, our discussion does not differentiate between a finite or a denumerably infinite number of states so that no special treatment is given to the former case.
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