GitHub

Bayesian Logistic Regression for Diabetes Prediction

This project explores the application of Bayesian Logistic Regression for binary classification, using a real-world dataset to predict diabetes outcomes. Developed as part of a statistical modeling ...
Frontiers

Bayesian Rician Regression for Neuroimaging

It is well-known that data from diffusion weighted imaging (DWI) follow the Rician distribution. The Rician distribution is also relevant for functional magnetic resonance imaging (fMRI) data obtained ...
Europe PMC

Bayesian additive regression trees for multivariate skewed responses.

Do data resources managed by EMBL-EBI and our collaborators make a difference to your work? If so, please take 10 minutes to fill in our survey, and help us make the case for why sustaining open data ...
Frontiers

A Bayesian Semiparametric Regression Model for Joint Analysis of Microbiome Data

1 Department of Applied Mathematics and Statistics, University of California, Santa Cruz, Santa Cruz, CA, United States 2 Department of Ocean Sciences, University of California, Santa Cruz, Santa Cruz ...
GitHub

LOWESS-Ridge-Lasso-ElasticNet-Bayesian-Regression.

The Ordinary Least Squares (OLS) method is one of the most commonly used techniques for regression analysis. Ordinary least squares (OLS) is a linear regression technique used to find the best-fitting ...
IEEE

Bayesian Regression With Network Prior: Optimal Bayesian Filtering Perspective

Abstract: The recently introduced intrinsically Bayesian robust filter (IBRF) provides fully optimal filtering relative to a prior distribution over an uncertainty class of joint random process models ...