MaximumEntropy and Bayesian Methods in Science and Engineering [EBook] : Foundations / edited by Gary J. Erickson, C. Ray Smith.
MaximumEntropy and Bayesian Methods in Science and Engineering [EBook] : Foundations / edited by Gary J. Erickson, C. Ray Smith.
This volume has its origin in the Fifth, Sixth and Seventh Workshops on and Bayesian Methods in Applied Statistics", held at "MaximumEntropy the University of Wyoming, August 58, 1985, and at Seattle University, August 58, 1986, and August 47, 1987. It was anticipated that the proceedi...
Personal Name(s):  Erickson, Gary J., (editor) 

Smith, C. Ray, (editor)  
Imprint: 
Dordrecht :
Springer,
1988

Physical Description: 
X, 314 p. 17 illus. online resource. 
Note: 
englisch 
ISBN: 
9789400930490 
DOI: 
10.1007/9789400930490 
Series Title: 
Fundamental Theories of Physics, An International Book Series on The Fundamental Theories of Physics: Their Clarification, Development and Application ;
3132 
Subject (LOC):  
Full Text 
Table of Contents:
 How does the Brain Do Plausible Reasoning?
 The Relation of Bayesian and Maximum Entropy Methods
 An Engineer Looks at Bayes
 Bayesian Inductive Inference and Maximum Entropy
 Excerpts from Bayesian Spectrum Analysis and Parameter Estimation
 Detection of ExtraSolar System Planets
 Stochastic Complexity and the Maximum Entropy Principle
 The Axioms of Maximum Entropy
 Understanding Ignorance
 Maximum Entropy Calculations on a Discrete Probability Space
 Quantum Density Matrix and Entropic Uncertainty
 InformationTheoretical Generalization of the Uncertainty Principle
 Time, Energy, and the Limits of Measurement
 On a Detection Estimator Related to Entropy
 The Evolution of Carnot’s Principle
 A Logic of Information Systems
 Methodological Principles of Uncertainty in Inductive Modelling: A New Perspective
 Comparison of Minimum CrossEntropy Inference with Minimally Informative Information Systems.