"Bayesian Inference" ed. by Javier Prieto Tejedor

This book takes a look at both theoretical foundations of Bayesian inference and practical implementations in different fields. It is intended as an introductory guide for the application of Bayesian inference in the fields of life sciences, engineering, and economics, as well as a source document of fundamentals for intermediate Bayesian readers.

The range of Bayesian inference algorithms and their different applications has been greatly expanded since the first implementation of a Kalman filter by Stanley F. Schmidt for the Apollo program. Extended Kalman filters or particle filters are just some examples of these algorithms that have been extensively applied to logistics, medical services, search and rescue operations, or automotive safety, among others.

Contents
1 Bayesian Inference Application
2 Node-Level Conflict Measures in Bayesian Hierarchical Models Based on Directed Acyclic Graphs
3 Classifying by Bayesian Method and Some Applications
4 Hypothesis Testing for High-Dimensional Problems
5 Bayesian vs Frequentist Power Functions to Determine the Optimal Sample Size: Testing One Sample Binomial Proportion Using Exact Methods
6 Converting Graphic Relationships into Conditional Probabilities in Bayesian Network
7 Bayesian Estimation of Multivariate Autoregressive Hidden Markov Model with Application to Breast Cancer Biomarker Modeling
8 Bayesian Model Averaging and Compromising in Dose-Response Studies
9 Two Examples of Bayesian Evidence Synthesis with the Hierarchical Meta-Regression Approach
10 Bayesian Modeling in Genetics and Genomicsvvv
11 Bayesian Two-Stage Robust Causal Modeling with Instrumental Variables using Student's t Distributions
12 Bayesian Hypothesis Testing: An Alternative to Null Hypothesis Significance Testing (NHST) in Psychology and Social Sciences
13 Bayesian Inference and Compressed Sensing
14 Sparsity in Bayesian Signal Estimation
15 Dynamic Bayesian Network for Time-Dependent Classification Problems in Robotics
16 A Bayesian Model for Investment Decisions in Early Ventures
17 Recent Advances in Nonlinear Filtering with a Financial Application to Derivatives Hedging under Incomplete Information
18 Airlines Content Recommendations Based on Passengers' Choice Using Bayesian Belief Networks