IEEE

Restricted Bayesian Lasso Regression With Inequality Constraints

Abstract: In this article, we investigate the utilization of the restricted Bayesian lasso regression, focusing on high-dimensional models that incorporate linear inequality constraints on the ...
Scientific Research Publishing

Rahman, A. and Khan, S. (2007) Prediction Distribution for Linear Regression Model with Multivariate Student-T Errors under the Bayesian Approach.

ABSTRACT: Egg loss is one of the major problems in the egg hatching industry. This study aims to support farmers in optimizing their egg hatch through the development of a prediction model. This is to ...
Hosted on MSN

Python Physics; Building a Linear Regression Function in VPython

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...
Hosted on MSN

Linear Regression In Python From Scratch | Simply Explained

Implement Linear Regression in Python from Scratch ! In this video, we will implement linear regression in python from scratch. We will not use any build in models, but we will understand the code ...
Hackaday

linear regression

Although [Vitor Fróis] is explaining linear regression because it relates to machine learning, the post and, indeed, the topic have wide applications in many things that we do with electronics and ...
C&EN

ProcessOptimizer, an Open-Source Python Package for Easy Optimization of Real-World Processes Using Bayesian Optimization: Showcase of Features and Example of Use

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...
GitHub

weighted-least-squares

Various codes centered around problems in Bayesian inference, Bayesian Linear Regression, and Bayesian Non-Linear Parameter Estimation using the application of various Markov Chain Monte Carlo ...
Scientific Research Publishing

Hahn, P.R., Murray, J.S. and Carvalho, C.M. (2020) Bayesian Regression Tree Models for Causal Inference: Regularization, Confounding, and Heterogeneous Effects (with Discussion ...

ABSTRACT: This study explores the application of Bayesian econometrics in policy evaluation through theoretical analysis. The research first reviews the theoretical foundations of Bayesian methods, ...