Strategic Economic Decision-Making: Using Bayesian Belief Networks to Solve Complex Problems: 9 - Brossura

Grover, Jeff

Brossura

ISBN 10: 1461460395 ISBN 13: 9781461460398

Casa editrice: Springer, 2012

Riassunto

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.

Su questo libro

Dalla quarta di copertina

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.

Dettagli dell'edizione

• Editore: Springer
• Data di pubblicazione: 2012
• Lingua: Inglese
• ISBN 10: 1461460395
• ISBN 13: 9781461460398
• Rilegatura: Copertina flessibile
• Numero di pagine: 128
• Contatto del produttore: ProductSafety@springernature.com; ProductSafety@springernature.com; ; Poststr. 9; Darmstadt; 64293; Germania