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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 Flow and Diffusion Images from Bayesian Spectral Analysis of Motion-Encoded NMR Data
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    Chapter 2 Bayesian Estimation of MR Images from Incomplete Raw Data
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    Chapter 3 Quantified Maximum Entropy and Biological EPR Spectra
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    Chapter 4 The Vital Importance of Prior Information for the Decomposition of Ion Scattering Spectroscopy Data
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    Chapter 5 Bayesian Consideration of the Tomography Problem
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    Chapter 6 Using MaxEnt to Determine Nuclear Level Densities
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    Chapter 7 A Fresh Look at Model Selection in Inverse Scaterring
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    Chapter 8 The Maximum-Entropy Method in Small-Angle Scattering
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    Chapter 9 Maximum Entropy Multi-Resolution EM Tomography by Adaptive Subdivision
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    Chapter 10 High Resolution Image Construction from IRAS Survey — Parallelization and Artifact Suppression
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    Chapter 11 Maximum Entropy Performance Analysis Of Spread-Spectrum Multiple-Access Communications
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    Chapter 12 Noise Analysis in Optical Fibre Sensing: A Study using the Maximum Entropy Method
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    Chapter 13 Autoclass — A Bayesian Approach to Classification
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    Chapter 14 Evolution Review Of BayesCalc, A Mathematica ™ Package for doing Bayesian Calculations
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    Chapter 15 Bayesian Inference for Basis Function Selection in Nonlinear System Identification using Genetic Algorithms
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    Chapter 16 The meaning of the word “Probability”
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    Chapter 17 The Hard Truth
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    Chapter 18 Are the Samples Doped — If so, How Much?
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    Chapter 19 Confidence Intervals from one Observation
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    Chapter 20 Hyothesis Refinement
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    Chapter 21 Bayesian Density Estimation
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    Chapter 22 Scale Invariant Markov Models for Bayesian Inversion of Linear Inverse Problems
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    Chapter 23 Foundations: Indifference, Independence & MaxEnt
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    Chapter 24 The Maximum Entropy on the Mean Method, Noise and Sensitivity
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    Chapter 25 The Maximum Entropy Algorithm Applied to the Two-Dimensional Random Packing Problem
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    Chapter 26 Bayesian Comparison of Models for Images
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    Chapter 27 Interpolation Models with Multiple Hyperparameters
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    Chapter 28 Density Networks and their Application to Protein Modelling
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    Chapter 29 The Cluster Expansion: A Hierarchical Density Model
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    Chapter 30 The Partitioned Mixture Distribution: Multiple Overlapping Density Models
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    Chapter 31 Generating Functional for the BBGKY Hierarchy and the N-Identical-Body Problem
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    Chapter 32 Entropies for Continua: Fluids and Magnetofluids
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    Chapter 33 A Logical Foundation for Real Thermodynamics
Attention for Chapter 19: Confidence Intervals from one Observation
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Chapter title
Confidence Intervals from one Observation
Chapter number 19
Book title
Maximum Entropy and Bayesian Methods
Published by
Springer Netherlands, January 1996
DOI 10.1007/978-94-009-0107-0_19
Book ISBNs
978-9-40-106534-4, 978-9-40-090107-0
Authors

C. C. Rodríguez

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 40%
Student > Ph. D. Student 4 27%
Professor 2 13%
Student > Master 1 7%
Other 1 7%
Other 0 0%
Unknown 1 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 27%
Engineering 3 20%
Computer Science 2 13%
Mathematics 1 7%
Economics, Econometrics and Finance 1 7%
Other 3 20%
Unknown 1 7%