Marketing analytics is a diverse field, with both academic researchers and practitioners
coming from a range of backgrounds including marketing, expert systems, statistics, and …

In the broad sphere of Analytics, prescriptive analytics is one of the emerging areas of
interest for both academicians and practitioners. As prescriptive analytics has transitioned …

We introduce a mixture of generalized hyperbolic distributions as an alternative to the
ubiquitous mixture of Gaussian distributions as well as their near relatives within which the …

Motivation: In recent years, work has been carried out on clustering gene expression
microarray data. Some approaches are developed from an algorithmic viewpoint whereas …

In this chapter, the basic concepts of clustering are introduced. Moreover, the most relevant
decisions to be made for the practical application of clustering methods are listed and briefly …

A mixture of shifted asymmetric Laplace distributions is introduced and used for clustering
and classification. A variant of the EM algorithm is developed for parameter estimation by …

The last decade has seen an explosion of work on the use of mixture models for clustering.
The use of the Gaussian mixture model has been common practice, with constraints …

A mixture of multivariate contaminated normal distributions is developed for model‐based
clustering. In addition to the parameters of the classical normal mixture, our contaminated …

This paper introduces a finite mixture of canonical fundamental skew tt (CFUST) distributions
for a model-based approach to clustering where the clusters are asymmetric and possibly …

Clustering is the process of finding underlying group structures in data. Although mixture
model-based clustering is firmly established in the multivariate case, there is a relative …