Strategic Economic Decision-Making: Using Bayesian Belief Networks to Solve Complex Problems

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Springer Science & Business Media, Dec 5, 2012 - Mathematics - 116 pages

Strategic Economic Decision-Making: Using Bayesian Belief Networks to Solve Complex Problems is a quick primer on the topic that introduces readers to the basic complexities and nuances associated with learning Bayes’ theory and inverse probability for the first time. This brief is meant for non-statisticians who are unfamiliar with Bayes’ theorem, walking them through the theoretical phases of set and sample set selection, the axioms of probability, probability theory as it pertains to Bayes’ theorem, and posterior probabilities. All of these concepts are explained as they appear in the methodology of fitting a Bayes’ model, and upon completion of the text readers will be able to mathematically determine posterior probabilities of multiple independent nodes across any system available for study. Very little has been published in the area of discrete Bayes’ theory, and this brief will appeal to non-statisticians conducting research in the fields of engineering, computing, life sciences, and social sciences.

 

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Contents

An Introduction to Bayes Theorem and Bayesian Belief Networks BBN
1
A Literature Review of Bayes Theorem and Bayesian Belief Networks BBN
10
Statistical Properties of Bayes Theorem
29
Bayesian Belief Networks BBN Experimental Protocol
43
Manufacturing Example
49
Political Science Example
55
Gambling Example
60
Publicly Traded Company Default Example
67
Insurance Risk Levels Example
73
Acts of Terrorism AOT Example
79
Currency Wars Example
85
College Entrance Exams Example
91
Special Forces Assessment and Selection SFAS OneStage Example
96
Special Forces Assessment and Selection SFAS TwoStage Example
103
Index
114
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