A Bayesian approach to classification accuracy inference

Bayesian approach to inference of population structure

Methods of inferring the population structure‎, ‎its applications in identifying disease models as well as foresighting the physical and mental situation of human beings have been finding ever-increasing importance‎. ‎In this article‎, ‎first‎, ‎motivation and significance of studying the problem of population structure is explained‎. ‎In the next section‎, ‎the applications of inference of p...

A PAC-Bayesian approach to adaptive inference

A Computational Approach to Bayesian Inference

xxx Although the Bayesian approach provides a complete solution to model-based analysis, it is often difficult to obtain closed-form solutions for complex models. However, numerical solutions to Bayesian modeling problems are now becoming attractive because of the advent of powerful, low-cost computers and new algorithms. We describe a general-purpose implementation of the Bayesian methodology ...

A Simulated Annealing Approach to Bayesian Inference

A generic algorithm for the extraction of probabilistic (Bayesian) information about model parameters from data is presented. The algorithm propagates an ensemble of particles in the product space of model parameters and outputs. Each particle update consists of a random jump in parameter space followed by a simulation of a model output and a Metropolis acceptance/rejection step based on a comp...

Functional Brain Response to Emotional Muical Stimuli in Depression, Using INLA Approach for Approximate Bayesian Inference

Introduction: One of the vital skills which has an impact on emotional health and well-being is the regulation of emotions. In recent years, the neural basis of this process has been considered widely. One of the powerful tools for eliciting and regulating emotion is music. The Anterior Cingulate Cortex (ACC) is part of the emotional neural circuitry involved in Major Depressive Disorder (MDD)....