Model theory of stochastic processes
Author(s)
Bibliographic Information
Model theory of stochastic processes
（Lecture notes in logic, 14）
Association for Symbolic Logic, c2002
- : hbk
- : pbk
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Note
Includes bibliographical references (p. 131-135) and index
Description and Table of Contents
- Volume
-
: hbk ISBN 9781568811673
Description
This book presents new research in probability theory using ideas from mathematical logic. It is a general study of stochastic processes on adapted probability spaces, employing the concept of similarity of stochastic processes based on the notion of adapted distribution. The authors use ideas from model theory and methods from nonstandard analysis. The construction of spaces with certain richness properties, defined by insights from model theory, becomes easy using nonstandard methods, but remains difficult or impossible without them.
Table of Contents
Dedication, Introduction, Chapter 1: Adapted Distributions, Chapter 2: Hyperfinite Adapted Spaces, Chapter 3: Saturated Spaces, Chapter 4: Comparing Stochastic Processes, Chapter 5: Definability in Adapted Spaces, Chapter 6: Elementary Extensions, Chapter 7: Rich Adapted Spaces, Chapter 8: Adapted Neometric Spaces, Chapter 9: Enlarging Saturated Spaces, References
- Volume
-
: pbk ISBN 9781568811727
Description
This book presents new research in probability theory using ideas from mathematical logic. It is a general study of stochastic processes on adapted probability spaces, employing the concept of similarity of stochastic processes based on the notion of adapted distribution. The authors use ideas from model theory and methods from nonstandard analysis. The construction of spaces with certain richness properties, defined by insights from model theory, becomes easy using nonstandard methods, but remains difficult or impossible without them.
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