2 citations · 3 across the 8 of their papers we have counts for
3 papers · 2 filters
Parsimonious Mixtures of Matrix Variate Bilinear Factor Analyzers
Michael P. B. Gallaugher, Paul D. McNicholas
Over the years, data have become increasingly higher dimensional, which has prompted an increased need for dimension reduction techniques. This is perhaps especially true for clust…
Assessing and Visualizing Matrix Variate Normality
Nikola Pocuca, Michael P. B. Gallaugher, Katharine M. Clark +1
A framework for assessing the matrix variate normality of three-way data is developed. The framework comprises a visual method and a goodness of fit test based on the Mahalanobis s…
Flexible Clustering with a Sparse Mixture of Generalized Hyperbolic Distributions
Alexa A. Sochaniwsky, Michael P. B. Gallaugher, Yang Tang +1
Robust clustering of high-dimensional data is an important topic because clusters in real datasets are often heavy-tailed and/or asymmetric. Traditional approaches to model-based c…