In this paper, an integrated model interpolation and extrapolation framework based on Bayesian inference and Response Surface Models (RSM) is proposed to validate the designs both within and outside ...

We are in this paper concerned with Bayesian inference in a counting process model where the intensities depend on an unknown parameter. In particular, the model gives a unified approach to Bayesian ...

Think of all those HPC simulators that people have been using for decades. These can be considered as software that implicitly define probabilistic generative models, or forward models, that go from ...

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 ...

Default prior choices fixing Zellner's g are predominant in the Bayesian Model Averaging literature, but tend to concentrate posterior mass on a tiny set of models. The paper demonstrates this ...