Overview

Full Product Details

Author:   Jeff Grover
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2016
Dimensions:   Width: 15.50cm , Height: 1.80cm , Length: 23.50cm
Weight:   5.561kg
ISBN:  

9783319484136

ISBN 10:   3319484133
Pages:   260
Publication Date:   12 January 2017
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

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.

Reviews

Author Information

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.

Tab Content 6

Author Website:  

Customer Reviews

Recent Reviews

No review item found!

Add your own review!

Countries Available

All regions