Intro; Preface; Contents; Contributors; Quantum Phases in Entropic Dynamics; 1 Introduction; 2 Entropic Dynamics
A Brief Review; 3 Gauge Symmetry and Multi-Valued Phases; 4 Discussion; References; Bayesian Approach to Variable Splitting Forward Models; 1 Introduction; 2 Forward Model 1; 3 Forward Model 2; 4 Forward Model 3; 5 Forward Models 4 and 5; 6 Forward Models 6 and 7; 7 Conclusions; References; Prior Shift Using the Ratio Estimator; 1 Introduction; 2 Setting and Goals; 3 Quantification Methods; 3.1 The Classify and Count Estimator (CCE); 3.2 The Ratio Estimator (RE); 4 Experiments

5 Final DiscussionReferences; Bayesian Meta-Analytic Measure; 1 Introduction; 2 Meta-Analysis Measure; 3 Example; 4 Final Remarks; References; Feature Selection from Local Lift Dependence-Based Partitions; 1 Introduction; 2 Local Lift Dependence; 3 Feature Selection Algorithm from Local Lift Dependence-Based Partitions; 3.1 Classical Feature Selection Algorithm; 3.2 Local Lift Dependence-Based Partitions; 3.3 Cost Functions; 3.4 Stopping Criteria for the Algorithm; 4 Applications; 5 Final Remarks; References; Probabilistic Inference of Surface Heat Flux Densities from Infrared Thermography

1 Introduction2 The Measurement System; 3 Forward Model; 3.1 Heat Diffusion; 3.2 Measurement System; 4 Heatflux Model: Adaptive Kernel; 4.1 Effective Number of Degrees of Freedom (eDOF); 5 Exploring the Parameter Space; 6 Synthetic Data as Benchmark; 7 Processing Measured Data; 8 Conclusions; References; Schrödinger's Zebra: Applying Mutual Information Maximization to Graphical Halftoning; 1 Introduction; 2 Information Theory and Halftoning; 3 Quantum Halftoning; 4 Implementation and Examples; 5 Obtaining Insights Regarding Human Vision; 6 Conclusion; References

Regression of Fluctuating System Properties: Baryonic Tully-Fisher Scaling in Disk Galaxies1 Introduction; 2 GLS Regression: Principles and Motivation; 3 Application of GLS to Tully-Fisher Scaling; 3.1 The Baryonic Tully-Fisher Relation; 3.2 Regression Analysis; 4 Conclusion; References; Bayesian Portfolio Optimization for Electricity Generation Planning; 1 Introduction; 2 Classical Approach; 3 Bayesian Approach; 3.1 Improper Prior Case; 3.2 Proper Prior Case; 4 Results; 5 Final Remarks; References; Bayesian Variable Selection Methods for Log-Gaussian Cox Processes; 1 Introduction

2 Spatial Point Pattern Process2.1 Log-Gaussian Cox Process; 3 Bayesian Variable Selection; 3.1 Kuo and Mallick (KM); 3.2 Gibbs Variable Selection (GVS); 3.3 Stochastic Search Variable Selection (SSVS); 3.4 Comparing the Methods; 4 Simulation Study; 4.1 Prior Distributions; 4.2 Landscapes Definitions; 4.3 Results; 5 Conclusion; References; Effect of Hindered Diffusion on the Parameter Sensitivity of Magnetic Resonance Spectra; 1 Introduction; 2 Magnetic Resonance; 3 Hindered Diffusion; 3.1 Recurrence; 3.2 Coordinate Systems; 4 Simple Model; 5 Discussion; References