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|a 9789811002724
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|a 10.1007/978-981-10-0272-4
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|a 519.2
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|a Itô, Kiyosi.
|e author.
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|4 http://id.loc.gov/vocabulary/relators/aut
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|a Poisson Point Processes and Their Application to Markov Processes
|h [electronic resource] /
|c by Kiyosi Itô.
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|a 1st ed. 2015.
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|a Singapore :
|b Springer Nature Singapore :
|b Imprint: Springer,
|c 2015.
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|a XI, 43 p. 3 illus.
|b online resource.
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|a text
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|a SpringerBriefs in Probability and Mathematical Statistics,
|x 2365-4341
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|a An extension problem (often called a boundary problem) of Markov processes has been studied, particularly in the case of one-dimensional diffusion processes, by W. Feller, K. Itô, and H. P. McKean, among others. In this book, Itô discussed a case of a general Markov process with state space S and a specified point a ∈ S called a boundary. The problem is to obtain all possible recurrent extensions of a given minimal process (i.e., the process on S \ {a} which is absorbed on reaching the boundary a). The study in this lecture is restricted to a simpler case of the boundary a being a discontinuous entrance point, leaving a more general case of a continuous entrance point to future works. He established a one-to-one correspondence between a recurrent extension and a pair of a positive measure k(db) on S \ {a} (called the jumping-in measure and a non-negative number m< (called the stagnancy rate). The necessary and sufficient conditions for a pair k, m was obtained so that the correspondence is precisely described. For this, Itô used, as a fundamental tool, the notion of Poisson point processes formed of all excursions of the process on S \ {a}. This theory of Itô's of Poisson point processes of excursions is indeed a breakthrough. It has been expanded and applied to more general extension problems by many succeeding researchers. Thus we may say that this lecture note by Itô is really a memorial work in the extension problems of Markov processes. Especially in Chapter 1 of this note, a general theory of Poisson point processes is given that reminds us of Itô's beautiful and impressive lectures in his day.
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|a Probabilities.
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|a Measure theory.
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|a Functional analysis.
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|a Probability Theory.
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|a Measure and Integration.
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|a Functional Analysis.
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|a SpringerLink (Online service)
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|t Springer Nature eBook
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|i Printed edition:
|z 9789811002717
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|i Printed edition:
|z 9789811002731
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|a SpringerBriefs in Probability and Mathematical Statistics,
|x 2365-4341
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|u https://doi.uam.elogim.com/10.1007/978-981-10-0272-4
|z Texto Completo
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|a ZDB-2-SMA
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|a ZDB-2-SXMS
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|a Mathematics and Statistics (SpringerNature-11649)
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|a Mathematics and Statistics (R0) (SpringerNature-43713)
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