Bayesian Model Averaging (BMA) provides a coherent mechanism to address the problem of model uncertainty. In this paper we extend the BMA framework to panel data models where the lagged dependent ...

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 ...

This article presents a Bayesian method for estimating nonparametrically a high-dimensional multinomial regression model. The regression functions are expressed as sums of main effects and ...

Weather predictions are uncertain by nature. This uncertainty is dynamically assessed by a finite set of trajectories, called ensemble members. Unfortunately, ensemble prediction systems underestimate ...

Bayesian prediction and modeling have emerged as transformative tools in the design and management of clinical trials. By integrating prior knowledge with accumulating trial data, Bayesian methods ...