Crossed Linear Gaussian Bayesian Networks, parsimonious models

This algorithm can be used in this context as linear mixed models can be put in the more general framework of models with incomplete data.. Among the CM-steps, one is dedicated to

Keywords: linear regression, Bayesian inference, generalized least-squares, ridge regression, LASSO, model selection criterion,

We first investigate the order of magnitude of the worst-case risk of three types of estimators of a linear functional: the greedy subset selection (GSS), the group (hard and

We show that under a suitable condition on the design matrix, the number of nonzero coefficients of the Lasso solution is an unbiased estimate for the degrees of freedom.. An

Subsequently, it was shown how linear dy- namic system models can be augmented with proba- bilistic variables for uncertain parameters, transform- ing them into dynamic

In this respect, Gianola et al (1992) proposed a Bayesian procedure to estimate heterogeneous variance components. Their approach can be viewed as a..

4.1. Main propositions used in this proof. The first result we will prove is the next theorem, which is an ℓ 1 -ball mixture multivariate regression model selection theorem for ℓ

Paradigm Shifts, Silver Tsunami, Creative Ageing Cities While there are a number of sources of current paradigm shifts towards what this volume calls Creative Ageing Cities