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The Manual of Strategic Economic Decision Making

Using Bayesian Belief Networks to Solve Complex Problems
BuchGebunden
260 Seiten
Englisch
Springererschienen am12.01.20171st ed. 2016
This book is an extension of the author´s first book and serves as a guide and manual on how to specify and compute 2-, 3-, and 4-Event Bayesian Belief Networks (BBN).mehr
Verfügbare Formate
BuchKartoniert, Paperback
EUR80,24
BuchGebunden
EUR80,24
E-BookPDF1 - PDF WatermarkE-Book
EUR80,24

Produkt

KlappentextThis book is an extension of the author´s first book and serves as a guide and manual on how to specify and compute 2-, 3-, and 4-Event Bayesian Belief Networks (BBN).
Details
ISBN/GTIN978-3-319-48413-6
ProduktartBuch
EinbandartGebunden
Verlag
Erscheinungsjahr2017
Erscheinungsdatum12.01.2017
Auflage1st ed. 2016
Seiten260 Seiten
SpracheEnglisch
Gewicht543 g
IllustrationenXXVIII, 260 p. 55 illus., 51 illus. in color.
Artikel-Nr.40215344

Inhalt/Kritik

Inhaltsverzeichnis
1. Introduction.- 1.1 Bayes' Theorem: An Introduction.- 1.2 Protocol.- 1.3 Data.- 1.4 Statistical Properties of Bayes' Theorem.- 1.5 Base Matrices.- 1.5.1 Event A Node.- 2. Base Matrices.- 2.1 Event A Node.- 2.1.1 Event A Node-Prior Counts.- 2.1.2 Module A-Prior Probabilities.- 2.2 Event B.- 2.2.1 Event B Node-Likelihood Counts.- 2.2.2 Module B Node.- 2.2.3 Event B Node-Counts.- 2.2.4 Event B Node-Likelihood Probabilities.- 2.3 Event C Node.- 2.3.1 Event C Node-Counts.- 2.3.2 Event C Node-Likelihood Probabilities.- 2.3.3 Event C Node-Counts.- 2.3.4 Event C Node-Likelihood Probabilities.- 2.3.5 Event C Node-Counts.- 2.3.6 Event C Node-Likelihood Probabilities.- 2.3.7 Event C Node-Counts.- 2.3.8 Event C Node-Probabilities.- 2.4 Event D Node.- 2.4.1 Event D Node-Counts.- 2.4.2 Event D Node-Likelihood Probabilities.- 2.5 Event D Node-Counts.- 2.5.1 Event D Node-Likelihood Probabilities.- 2.5.2 Event D Node-Counts.- 2.5.3 Event D Node-Likelihood Probabilities.- 2.5.4 Event D Node-Counts.- 2.5.5 Event D Node-Likelihood Probabilities.- 2.5.6 Event D Node-Counts.- 2.5.7 Event D Node-Likelihood Probabilities.- 2.5.8 Event D Node-Counts.- 2.5.9 Event D Node-Likelihood Probabilities.- 2.5.10 Event D Node-Counts.- 2.5.11 Event D Node-Likelihood Probabilities.- 3. 2-Event 1-Path BBN.- 3.1 [A] [B].- 3.1.1 2-Event BBN Proof.- 3.1.2 BBN Specification.- 4.3-Event 2-Path BBNs.- 4.1 [AB|AC].- 4.1.1 Proof.- 4.1.2 BBN Specification.- 4.2 [AC|BC].- 4.2.1 Proof.- 4.2.2 BBN Specification.- 4.3 [AB|BC].- 4.3.1 Proof.- 4.3.2 BBN Specification.- 5. 3-Event 3-Path BBNs.- 5.1 3-Paths-[AB|AC|BC].- 5.1.1 Proof.- 5.1.2 BBN Probabilities.mehr

Schlagworte

Autor

Jeff Grover,  Doctor of Business Administration (DBA) (Finance),   is Founder and Chief Research Scientist at Grover Group, Inc., where he specializes in Bayes´ Theorem and its application to strategic economic decision making through Bayesian Belief Networks (BBN). He specializes in blending economic theory and BBN to maximize stakeholder wealth. He is a winner of the Kentucky Innovation Award (2015) for the application of his proprietary BBN big data algorithm. He has operationalized BBN in the healthcare industry, evaluating the Medicare Hospital Compare data; in the Department of Defense, conducting research with U.S. Army Recruiting Command to determine optimal levels of required recruiters for recruiting niche market medical professionals; and in the agriculture industry in optimal soybean selection. In the area of economics, he was recently contracted by the Department of Energy, The Alliance for Sustainable Energy, LLC Management and Operating Contractor for the National Renewable Energy Laboratory, to conduct a 3rd party evaluation of the Hydrogen Financial Analysis Scenario (H2FAST) Tool.