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El. knyga: Set-Indexed Martingales

(University of Ottawa, Ontario, Canada), (Bar Ilan University, Ramat-Gan, Israel)
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Set-Indexed Martingales offers a unique, comprehensive development of a general theory of Martingales indexed by a family of sets. The authors establish-for the first time-an appropriate framework that provides a suitable structure for a theory of Martingales with enough generality to include many interesting examples.

Developed from first principles, the theory brings together the theories of Martingales with a directed index set and set-indexed stochastic processes. Part One presents several classical concepts extended to this setting, including: stopping, predictability, Doob-Meyer decompositions, martingale characterizations of the set-indexed Poisson process, and Brownian motion. Part Two addresses convergence of sequences of set-indexed processes and introduces functional convergence for processes whose sample paths live in a Skorokhod-type space and semi-functional convergence for processes whose sample paths may be badly behaved.

Completely self-contained, the theoretical aspects of this work are rich and promising. With its many important applications-especially in the theory of spatial statistics and in stochastic geometry- Set Indexed Martingales will undoubtedly generate great interest and inspire further research and development of the theory and applications.

Recenzijos

"a small, elegant volumeThis state-of-the-art monograph will be a valuable resource and stimulus for further work in the area." -Short Book Reviews of the ISI "I would recommend the book as an excellent introduction to set-indexed martingales. The foundations of the general theory are clearly presented and the reader is led to a point that is close to the current edge of research." --Simon Harris, University of Bath

Introduction 1(6)
I General Theory 7(124)
Generalities
9(26)
Framework and Assumptions
9(6)
Examples
15(4)
The Hausdorff Metric
19(3)
The Probability Structure
22(6)
Stopping Sets
28(7)
Predictability
35(18)
A characterization by stochastic intervals
35(5)
Announcability
40(3)
Progressivity
43(4)
Left-continuous processes
47(6)
Martingales
53(20)
Definitions
54(3)
Classical properties
57(4)
Stopping theorems
61(5)
Examples
66(7)
Decompositions and Quadratic Variation
73(24)
Definitions
73(1)
Admissible Functions and Measures
74(7)
Compensator and Quadratic Variation
81(5)
Discrete Approximations
86(5)
Point Processes and Compensators
91(6)
Martingale Characterizations
97(16)
Flows
98(8)
Brownian Motion
106(1)
The Poisson Process
107(6)
Generalizations of Martingales
113(18)
Local Martingales
114(2)
Doob-Meyer Decompositions
116(3)
Quasimartingales
119(12)
II Weak Convergence 131(56)
Weak Convergence of Set-Indexed Processes
133(18)
The Function Space D(A)
134(10)
Weak Convergence on D(A)
144(3)
Semi-Functional Convergence
147(4)
Limit Theorems for Point Processes
151(24)
Strictly simple point processes
152(8)
Poisson limit theorem
160(9)
Empirical processes
169(6)
Martingale Central Limit Theorems
175(12)
Central Limit Theorems
175(6)
The Weighted Empirical Process
181(6)
References 187(20)
Index 207


Gail Ivanoff, Professor of Mathematics and Statistics, University of Ottawa, Ontario, Canada. Ely Merzbach, Professor of Mathematics and Computer Science, Bar-Ilan University, Ramat Gan, Israel.