Poisson Processes

by
Format: Hardcover
Pub. Date: 1993-01-28
Publisher(s): Clarendon Press
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Summary

Two fundamental theories are commonly debated in the study of random processes: the Bachelier Wiener model of Brownian motion, which has been the subject of many books, and the Poisson process. While nearly every book mentions the Poisson process, most hurry past to more general point processes or to Markov chains. This comparative neglect is ill judged, and stems from a lack of perception of the real importance of the Poisson process. This distortion partly comes about from a restriction to one dimension, while the theory becomes more natural in more general contexts. This book attempts to redress the balance. It records the author's fascination with the beauty and wide applicability of Poisson processes in one or more dimensions. The mathematical theory is powerful and a few key results often produce surprising consequences.

Table of Contents

Stochastic models for random sets of points
1(10)
Poisson models
1(2)
The Poisson distribution
3(4)
Probability spaces for Poisson processes
7(2)
The inevitability of the Possion distribution
9(2)
Poisson processes in general spaces
11(14)
Definition and basic properties
11(3)
The Superposition Theorem
14(3)
The Mapping Theorem
17(4)
The Bernoulli process
21(2)
The Existence Theorem
23(2)
Sums over Poisson processes
25(13)
Means, variances, and distributions
25(3)
Campbell's Theorem
28(3)
The characteristic functional
31(2)
Renyi's Theorem
33(5)
Possion processes on the line
38(15)
Intervals of a homogeneous process
38(3)
The Law of Large Numbers
41(3)
Queues
44(3)
Bartlett's Theorem
47(3)
Non-homogeneous processes
50(3)
Marked Poisson processes
53(12)
Colouring
53(2)
The product space representation
55(2)
Campbell's Theorem revisited
57(2)
The wide motorway
59(2)
Ecological models
61(2)
The orbital motorway
63(2)
Cox processes
65(8)
Definitions and basic properties
65(1)
Cox processes in ecology
66(2)
The Borel-Tanner distribution
68(3)
Cox processes and renewal processes
71(2)
Stochastic geometry
73(6)
Poisson processes of geometrical objects
73(1)
Line processes
74(3)
Cox line processes
77(1)
More general geometrical objects
77(2)
Completely random measures
79(11)
The canonical representation
79(3)
Construction from Poisson processes
82(2)
The Blackwell argument
84(3)
Subordinators
87(3)
The Poisson-Dirichlet distribution
90(10)
The Dirichlet distribution
90(2)
The Dirichlet process
92(1)
The Poisson-Dirichlet limit
93(1)
The Moran subordinator
94(2)
The Ewens sampling formula
96(2)
Size-biased sampling
98(2)
References 100(2)
Index of Theorems 102(1)
Subject index 103

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