Statistical inference in nested linear models that result from linear restrictions on the parameters of encompassing linear models can be considered to result from the conditional distribution under the encompassing model. We extend this reasoning to nested models that result from general...

This paper proposes a new estimator for least squares model averaging. A model average estimator is a weighted average of common estimates obtained from a set of models. We propose computing weights by minimizing a model average prediction criterion (MAPC). We prove that the MAPC estimator is...

The combination of graphical models and reference analysis represents a powerful tool for Bayesian inference in highly multivariate settings. It is typically difficult to derive reference priors in complex problems. In this paper we present a suitable mixed parameterisation for a discrete...

An increasing trend in functional MRI experiments involves discriminating between experimental conditions on the basis of fine-grained spatial patterns extending across many voxels. Typically, these approaches have used randomized resampling to derive inferences. Here, we introduce an analytical...

By means of a very simple example, this note illustrates the appeal of using Bayesian rather than classical methods to produce inference on hidden states in models of Markovian regime switching. -- Bayesian analysis ; switching regression ; regime changes ; nonlinear filtering