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Titlebook: Denumerable Markov Chains; with a chapter of Ma John G. Kemeny,J. Laurie Snell,Anthony W. Knapp Textbook 1976Latest edition Springer Scienc

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发表于 2025-3-21 16:39:48 | 显示全部楼层 |阅读模式
书目名称Denumerable Markov Chains
副标题with a chapter of Ma
编辑John G. Kemeny,J. Laurie Snell,Anthony W. Knapp
视频video
丛书名称Graduate Texts in Mathematics
图书封面Titlebook: Denumerable Markov Chains; with a chapter of Ma John G. Kemeny,J. Laurie Snell,Anthony W. Knapp Textbook 1976Latest edition Springer Scienc
描述With the first edition out of print, we decided to arrange for republi­ cation of Denumerrible Markov Ohains with additional bibliographic material. The new edition contains a section Additional Notes that indicates some of the developments in Markov chain theory over the last ten years. As in the first edition and for the same reasons, we have resisted the temptation to follow the theory in directions that deal with uncountable state spaces or continuous time. A section entitled Additional References complements the Additional Notes. J. W. Pitman pointed out an error in Theorem 9-53 of the first edition, which we have corrected. More detail about the correction appears in the Additional Notes. Aside from this change, we have left intact the text of the first eleven chapters. The second edition contains a twelfth chapter, written by David Griffeath, on Markov random fields. We are grateful to Ted Cox for his help in preparing this material. Notes for the chapter appear in the section Additional Notes. J.G.K., J.L.S., A.W.K.
出版日期Textbook 1976Latest edition
关键词Brownian motion; Chains; Markov; Markov chain; Markov property; Martingale; Random Walk; Random variable; St
版次2
doihttps://doi.org/10.1007/978-1-4684-9455-6
isbn_softcover978-1-4684-9457-0
isbn_ebook978-1-4684-9455-6Series ISSN 0072-5285 Series E-ISSN 2197-5612
issn_series 0072-5285
copyrightSpringer Science+Business Media New York 1976
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发表于 2025-3-21 22:05:40 | 显示全部楼层
Properties of Markov Chains,hat an arbitrary stochastic process may be considered as a process on a suitable . in which the outcome functions . are coordinate functions. We see, therefore, that in a sense no generality is lost by discussing Markov chains in terms of sequence space.
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Recurrent Chains,nt chains begins with a charac­terization of finite-valued non-negative superregular measures and functions; the reader should turn back to Sections 1-6c and 1-6d for the terms referred to in what follows.
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Introduction to Random Fields,in an arbitrary countable parameter set .. Roughly, a random field with denumerable state space . is described by a probability measure . on the space . = . of all configurations of values from . on the generalized time set .. In this chapter we discuss certain extensions of Markov chains, called .
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https://doi.org/10.1007/978-3-642-82595-8which have been important objects of study in the recent development of probability theory. Only some of the highlights of this rich theory will be covered; we concentrate especially on the case . the integers, where the connections with classical Markov chain theory are deepest.
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Introduction to Random Fields,which have been important objects of study in the recent development of probability theory. Only some of the highlights of this rich theory will be covered; we concentrate especially on the case . the integers, where the connections with classical Markov chain theory are deepest.
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