Abstract: In this paper, we review classical and advanced methodologies for analysing within-subject functional Magnetic Resonance Imaging (fMRI) data. Such data are usually acquired during sensory or cognitive experiments that aims at stimulating the subject in the scanner and eliciting evoked...

In various frameworks, to assess the joint distribution of a k-dimensional random vector X=(X1,…,Xk), one selects some putative conditional distributions Q1,…,Qk. Each Qi is regarded as a possible (or putative) conditional distribution for Xi given (X1,…,Xi−1,Xi+1,…,Xk). The Qi are...

Models with structured additive predictor provide a very broad and rich framework for complex regression modeling. They can deal simultaneously with nonlinear covariate effects and time trends, unit- or cluster-specific heterogeneity, spatial heterogeneity and complex interactions between...

Space-varying regression models are generalizations of standard linear models where the regression coefficients are allowed to change in space. The spatial structure is specified by a multivariate extension of pairwise difference priors thus enabling incorporation of neighboring structures and...