Bayesian nonparametric mixture models represent a powerful statistical framework that extends traditional mixture modelling by allowing the number of mixture components to be inferred from the data ...

Genome-wide association studies often face the undesirable result of either failing to detect any influential markers at all because of a stringent level for testing ...

In this paper, we introduce a Bayesian approach for clustering data using a sparse finite mixture model (SFMM). The SFMM is a finite mixture model with a large number of components k previously fixed ...

In studying structural inter-connections in the human brain, it is common to first estimate fiber bundles connecting different regions relying on diffusion MRI. These fiber bundles act as highways for ...