The growth of biostatistics has been phenomenal in recent years and has been marked by
considerable technical innovation in both methodology and computational practicality. One …

This paper introduces the idea of drawing upon the cognitive neuroscience literature to
inform IS research (herein termed “NeuroIS”). Recent advances in cognitive neuroscience …

This research essay outlines a set of guidelines for conductingfunctional Magnetic
Resonance Imaging (fMRI) studies in social science research in general and also …

Recent work on functional magnetic resonance imaging large-scale brain networks under
resting conditions demonstrated its potential to evaluate the integrity of brain function under …

Many clustering methods, such as K-means, kernel K-means, and MNcut clustering, follow
the same recipe:(i) choose a measure of similarity between observations;(ii) define a figure …

In this article, we examine the development and use of covariate models where the relation
with explanantory covariates is spatially adaptive. In this way space is regarded as an effect …

Supplement to “The Gibbs-plaid biclustering model”. A high-resolution version of the image
shown in Figure 6, as well as the complete biclustering results associated with the RD data …

A Bayesian semi-parametric survival regression model with latent partitions is introduced. Its
goal is to predict survival and to cluster survival patients within the context of building …

This article presents a Bayesian kernel-based clustering method. The associated model
arises as an embedding of the Potts density for class membership probabilities into an …

Motivated by classes of problems frequently found in the analysis of gene expression data,
we propose a semiparametric Bayesian model to detect biclusters, that is, subsets of …