baysian-models

BSTVC-R is an R package for spatiotemporal heterogeneous analysis within a unified full-map framework. It supports the analysis of locally varying influencing factors, identification of key global drivers, and dynamic prediction, providing a programmable and reproducible workflow for spatiotemporal interpretable modeling.

Predicting risk factors by Determining Social Determinants of Health variables using a probabilistic model.

Extends the core methodology from "Large Bayesian Vector Auto Regressions" by Bańbura et al. (2010), focusing on how Bayesian shrinkage enables estimation of high-dimensional VARs without overfitting.

Open-source unified MMM interface

The repository houses the source code of paper

Case Study: Personalized Anti-Coagulation: Optimizing Warfarin Management Using Genetics and Simulated Clinical Trials