Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 76, No. 5 (NOVEMBER 2014), pp. 833-859 (27 pages) The choice of the summary statistics that are used in Bayesian ...

In objective Bayesian model selection, no single criterion has emerged as dominant in defining objective prior distributions. Indeed, many criteria have been separately proposed and utilized to ...

This paper extends the Bayesian Model Averaging framework to panel data models where the lagged dependent variable as well as endogenous variables appear as regressors. We propose a Limited ...

BhGLM is a freely available R package that implements Bayesian hierarchical modeling for high-dimensional clinical and genomic data. It consists of functions for setting up various Bayesian ...

The authors used a Bayesian modeling framework to fit behavior and serotonin neuron activity to reward history across multiple timescales. A key goal was to distinguish value coding from other ...

Bayesian networks are powerful tools in probabilistic reasoning, allowing us to model complex systems where uncertainty and causal relationships intertwine. At their core, Bayesian Networks are ...