Mixtures of shifted asymmetric Laplace distributions were introduced as ...
Bi-clustering is a technique that allows for the simultaneous clustering...
The human microbiome plays an important role in human health and disease...
Discrete data such as counts of microbiome taxa resulting from
next-gene...
Biclustering is used for simultaneous clustering of the observations and...
Mixtures of multivariate normal inverse Gaussian (MNIG) distributions ca...
Non-Gaussian mixture models are gaining increasing attention for mixture...
Multivariate count data are commonly encountered through high-throughput...
Three-way data structures, characterized by three entities, the units, t...
High-dimensional data of discrete and skewed nature is commonly encounte...
Parameter estimation for model-based clustering using a finite mixture o...
The expectation-maximization (EM) algorithm is an iterative method for
f...
Mixture model-based clustering has become an increasingly popular data
a...