UID:
almahu_9949384092702882
Format:
1 online resource (xxi, 637 pages)
Edition:
Second edition.
ISBN:
9781315269405
,
1315269406
,
9781351978972
,
1351978977
,
1351978969
,
9781351978965
Content:
Since the first edition of this book published, Bayesian networks have become even more important for applications in a vast array of fields. This second edition includes new material on influence diagrams, learning from data, value of information, cybersecurity, debunking bad statistics, and much more. Focusing on practical real-world problem-solving and model building, as opposed to algorithms and theory, it explains how to incorporate knowledge with data to develop and use (Bayesian) causal models of risk that provide more powerful insights and better decision making than is possible from purely data-driven solutions.
Note:
Introduction -- Debunking bad statistics -- The need for causal, explanatory models in risk assessment -- Measuring uncertainty: the inevitability of subjectivity -- The basics of probability -- Bayes' theorem and conditional probability -- From Bayes' theorem to Bayesian networks -- Defining the structure of Bayesian networks -- Building and eliciting node probability tables -- Numeric variables and continuous distribution functions -- Decision analysis, decision trees, value of information analysis, and sensitivity -- Hypothesis testing and confidence intervals -- Modeling operational risk -- Systems reliability modeling -- The role of Bayes in forensic and legal evidence presentation -- Building and using Bayesian networks for legal reasoning -- Learning from data in Bayesian networks.
Additional Edition:
Print version: Fenton, Norman E., 1956- Risk assessment and decision analysis with Bayesian networks. Boca Raton, FL : CRC Press, Taylor & Francis Group, [2019] ISBN 9781138035119
Language:
English
Subjects:
Economics
,
Mathematics
Keywords:
Electronic books.
;
Electronic books.
URL:
https://www.taylorfrancis.com/books/9781315269405
