Conditional Independence in Applied Probability

P. E. Pfeiffer

ISBN 10: 1461263379 / ISBN 13: 9781461263371

Published by Birkhäuser Boston Nov 2011, 2011

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware -It would be difficult to overestimate the importance of stochastic independence in both the theoretical development and the practical appli cations of mathematical probability. The concept is grounded in the idea that one event does not 'condition' another, in the sense that occurrence of one does not affect the likelihood of the occurrence of the other. This leads to a formulation of the independence condition in terms of a simple 'product rule,' which is amazingly successful in capturing the essential ideas of independence. However, there are many patterns of 'conditioning' encountered in practice which give rise to quasi independence conditions. Explicit and precise incorporation of these into the theory is needed in order to make the most effective use of probability as a model for behavioral and physical systems. We examine two concepts of conditional independence. The first concept is quite simple, utilizing very elementary aspects of probability theory. Only algebraic operations are required to obtain quite important and useful new results, and to clear up many ambiguities and obscurities in the literature. 168 pp. Englisch.

Seller Inventory # 9781461263371

Bibliographic Details

• Title: Conditional Independence in Applied Probability
• Publisher: Birkhäuser Boston Nov 2011
• Publication Date: 2011
• Language: English
• ISBN 10: 1461263379
• ISBN 13: 9781461263371
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 216W x 140H x 10D millimeters 216 millimeters width by 140 millimeters height by 10 millimeters depth
• Weight: 220 grams

About this title

Synopsis

It would be difficult to overestimate the importance of stochastic independence in both the theoretical development and the practical appli­ cations of mathematical probability. The concept is grounded in the idea that one event does not "condition" another, in the sense that occurrence of one does not affect the likelihood of the occurrence of the other. This leads to a formulation of the independence condition in terms of a simple "product rule," which is amazingly successful in capturing the essential ideas of independence. However, there are many patterns of "conditioning" encountered in practice which give rise to quasi independence conditions. Explicit and precise incorporation of these into the theory is needed in order to make the most effective use of probability as a model for behavioral and physical systems. We examine two concepts of conditional independence. The first concept is quite simple, utilizing very elementary aspects of probability theory. Only algebraic operations are required to obtain quite important and useful new results, and to clear up many ambiguities and obscurities in the literature.