Marine regression emerges as key driver of Late Paleozoic Ice Age in high-resolution model

Earth system box models are essential tools for reconstructing long-term climatic and environmental evolution and uncovering ...
Thorax

Disparities in lung function trajectories among tobacco-exposed individuals

Background The relationship of social determinants of health (SDOH), environmental exposures and medical history to lung function trajectories is underexplored. A better understanding of these ...
GitHub

psoerensen/bayesian-linear-regression

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 ...
Scientific Research Publishing

Linero, A.R. (2018) Bayesian Regression Trees for High-Dimensional Prediction and Variable Selection. Journal of the American Statistical Association, 113, 626-636.

ABSTRACT: This study investigates the persistent academic impacts of the Head Start program, a federal government-funded early childhood intervention, using data from the Early Childhood Longitudinal ...
Frontiers

Toward interpretable expected goals modeling using Bayesian mixed models

Empowered by technological progress, sports teams and bookmakers strive to understand relationships between player and team activity and match outcomes. For this purpose, the probability of an event ...
marktechpost

Embed-then-Regress: A Versatile Machine Learning Approach for Bayesian Optimization Using String-Based In-Context Regression

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.
The New York Times

Questions for Investigators Trying to Unravel Mystery of Luxury Yacht’s Sinking

The boat executive, Mr. Costantino, has argued that the Bayesian was an extremely safe vessel that could list even to 75 degrees without capsizing. His company, the Italian Sea Group, in 2022 bought ...
Scientific Research Publishing

Hill, J.L. (2011) Bayesian Nonparametric Modeling for Causal Inference. Journal of Computational and Graphical Statistics, 20, 217-240.

ABSTRACT: Modeling dynamic systems with linear parametric models usually suffer limitation which affects forecasting performance and policy implications. This paper advances a non-parametric ...