The Poisson process, a core object in modern probability, enjoys a richer theory than is sometimes appreciated. This volume develops the theory in the setting of a general abstract measure space, establishing basic results and properties as well as certain advanced topics in the stochastic analysis...

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Bibliographic Details

Main Author:	Last, Günter (Author)
Format:	Electronic eBook
Language:	English
Published:	Cambridge Cambridge University Press 2018
Series:	Institute of Mathematical Statistics textbooks 7
Subjects:	Poisson processes Stochastic processes Probabilities Poisson-Prozess
Online Access:	FHN01 BSB01 Volltext
Summary:	The Poisson process, a core object in modern probability, enjoys a richer theory than is sometimes appreciated. This volume develops the theory in the setting of a general abstract measure space, establishing basic results and properties as well as certain advanced topics in the stochastic analysis of the Poisson process. Also discussed are applications and related topics in stochastic geometry, including stationary point processes, the Boolean model, the Gilbert graph, stable allocations, and hyperplane processes. Comprehensive, rigorous, and self-contained, this text is ideal for graduate courses or for self-study, with a substantial number of exercises for each chapter. Mathematical prerequisites, mainly a sound knowledge of measure-theoretic probability, are kept in the background, but are reviewed comprehensively in the appendix. The authors are well-known researchers in probability theory; especially stochastic geometry. Their approach is informed both by their research and by their extensive experience in teaching at undergraduate and graduate levels
Item Description:	Title from publisher's bibliographic system (viewed on 10 Nov 2017)
Physical Description:	1 online resource (xx, 293 pages)
ISBN:	9781316104477
DOI:	10.1017/9781316104477