"New Insights into Bayesian Inference" ed. by Mohammad Saber Fallah Nezhad

This book is an introduction to the mathematical analysis of Bayesian decision-making when the state of the problem is unknown but further data about it can be obtained.

The objective of such analysis is to determine the optimal decision or solution that is logically consistent with the preferences of the decision-maker, that can be analyzed using numerical utilities or criteria with the probabilities assigned to the possible state of the problem, such that these probabilities are updated by gathering new information.



Contents
1 Introductory Chapter: Bayesian Thinking
2 Bayesian Modeling Approaches for Temporal Dynamics in RNA-seq Data
3 Bayesian Analysis for Hidden Markov Factor Analysis Models
4 Dynamic Process Model Parameter Estimation by Global System Analysis
5 Preventing Disparities: Bayesian and Frequentist Methods for Assessing Fairness in Machine-Learning Decision-Support Models
6 Using Bayesian Inference to Investigate the Influence of Environmental Factors on a Phytoplasma Disease
7 A Bayesian Hau-Kashvap Approach for Hepatitis Disease Detection