This repository includes theoretical notes, slides, and hands-on R examples for exploring Bayesian Linear Regression. It introduces both classical and Bayesian regression methods, showing how to ...

ABSTRACT: What role does credit allocation play in shaping economic performance in small, developing countries? While prior research shows that business credit tends to support growth and household ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...

Regression models with intractable normalizing constants are valuable tools for analyzing complex data structures, yet parameter inference for such models remains highly challenging—particularly when ...

Abstract: In this paper, we introduce an enhanced version of the Bayesian linear regression with Cauchy prior (BLRC) algorithm, as previously detailed in [1]. This refinement, termed efficient BLRC (E ...

Bayesian Optimization, widely used in experimental design and black-box optimization, traditionally relies on regression models for predicting the performance of solutions within fixed search spaces.

Abstract: Presents corrections to the paper, Bayesian Linear Regression With Cauchy Prior and Its Application in Sparse MIMO Radar.

Department of VMS-Pathobiology, University of Illinois Urbana—Champaign, Urbana, Illinois 61801, United States ...

Specifying accurate informative prior distributions is a question of carefully selecting studies that comprise the body of comparable background knowledge. Psychological research, however, consists of ...