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Maximum Entropy and Bayesian Methods

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Cover of 'Maximum Entropy and Bayesian Methods'

Table of Contents

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    Book Overview
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    Chapter 1 Probability Theory as Logic
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    Chapter 2 Probability Theory and the Associativity Equation
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    Chapter 3 Objective Bayesianism and Geometry
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    Chapter 4 Consistency Principle for Data-Based Probabilistic Inference
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    Chapter 5 An Introduction to Parameter Estimation Using Bayesian Probability Theory
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    Chapter 6 From Laplace to Supernova SN 1987A: Bayesian Inference in Astrophysics
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    Chapter 7 Atmospheric 14 C Variations: A Bayesian Prospect
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    Chapter 8 On Decoupling Probability from Kinematics in Quantum Mechanics
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    Chapter 9 Bayesian Model Selection and Parameter Estimation Applied to Sea Floor Pressure Data
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    Chapter 10 Applications of Maximum Entropy and Bayesian Methods in Neutron Scattering
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    Chapter 11 The Conditional Entropy of a Canonical Constraint
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    Chapter 12 Solving Oversampled Data Problems By Maximum Entropy
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    Chapter 13 Constructing Priors in Maximum Entropy Methods
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    Chapter 14 Maximum Entropy with Nonlinear Constraints: Physical Examples
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    Chapter 15 Maximum Entropy Description of Plasma Equilibrium
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    Chapter 16 Linear Inversion by the Maximum Entropy Method with Specific Non-Trivial Prior Information
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    Chapter 17 Minimum Dissipation And Maximum Entropy
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    Chapter 18 Maximum Entropy and Equations of State for Random Cellular Structures
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    Chapter 19 Delay Estimation using Maximum Entropy Derived Phase Information
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    Chapter 20 Drug Absorption in Man, and its Measurement by MaxEnt
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    Chapter 21 Quantified Maximum Entropy
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    Chapter 22 Quantified Maxent: An NMR Application
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    Chapter 23 Maximum Entropy Reconstruction of Radar Cross-Section Images
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    Chapter 24 FIER: A Filtered Entropy Approach to Maxium Entropy Image Restoration
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    Chapter 25 Regularisation in Coded-Aperture Spect
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    Chapter 26 Burg Algorithm Applied to Fourier Transform ION Cyclotron Resonance Mass Spectrometry
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    Chapter 27 Maximum Entropy Analysis for Pattern Recognition
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    Chapter 28 Application of Burg’s Spectral Analysis to Heave Response Modeling in Underwater Applications
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    Chapter 29 Maximum Entropy and Minimum Cross-Entropy Principles: Need for a Broader Perspective
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    Chapter 30 The Inverse MaxEnt and MinxEnt Principles and their Applications
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    Chapter 31 A Comprative Assessment of Entropic and Non-Entropic Methods of Estimation
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    Chapter 32 Maxent Applied To Linear Regression
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Title
Maximum Entropy and Bayesian Methods
Published by
Springer Netherlands, December 2012
DOI 10.1007/978-94-009-0683-9
ISBNs
978-9-40-106792-8, 978-9-40-090683-9
Editors

Fougère, Paul F.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 1 13%
Unknown 7 88%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 3 38%
Student > Ph. D. Student 2 25%
Professor 1 13%
Researcher 1 13%
Other 1 13%
Other 0 0%
Readers by discipline Count As %
Psychology 3 38%
Agricultural and Biological Sciences 2 25%
Biochemistry, Genetics and Molecular Biology 1 13%
Computer Science 1 13%
Physics and Astronomy 1 13%
Other 0 0%