Bayesian approaches to variable selection and model comparison construct a coherent probabilistic framework that integrates prior beliefs with observed data. In variable selection, each candidate ...

Bayesian inference for model selection centres on comparing competing hypotheses by evaluating how well each model explains observed data, accounting for prior beliefs about parameters. The ...

A novel Bayesian Hierarchical Network Model (BHNM) is designed for ensemble predictions of daily river stage, leveraging the spatial interdependence of river networks and hydrometeorological variables ...