171 citations · 214 across the 4 of their papers we have counts for
6 papers
Tackling the infinite likelihood problem when fitting mixtures of shifted asymmetric Laplace distributions
Yuan Fang, Brian C. Franczak, Sanjeena Subedi
Mixtures of shifted asymmetric Laplace distributions were introduced as a tool for model-based clustering that allowed for the direct parameterization of skewness in addition to lo…
Subspace Clustering with the Multivariate-t Distribution
Angelina Pesevski, Brian C. Franczak, Paul D. McNicholas
Clustering procedures suitable for the analysis of very high-dimensional data are needed for many modern data sets. In model-based clustering, a method called high-dimensional data…
A Mixture of Coalesced Generalized Hyperbolic Distributions
Cristina Tortora, Brian C. Franczak, Ryan P. Browne +1
A mixture of multiple scaled generalized hyperbolic distributions (MMSGHDs) is introduced. Then, a coalesced generalized hyperbolic distribution (CGHD) is developed by joining a ge…
Unsupervised Learning via Mixtures of Skewed Distributions with Hypercube Contours
Brian C. Franczak, Cristina Tortora, Ryan P. Browne +1
Mixture models whose components have skewed hypercube contours are developed via a generalization of the multivariate shifted asymmetric Laplace density. Specifically, we develop m…
Parsimonious Shifted Asymmetric Laplace Mixtures
Brian C. Franczak, Paul D. McNicholas, Ryan P. Browne +1
A family of parsimonious shifted asymmetric Laplace mixture models is introduced. We extend the mixture of factor analyzers model to the shifted asymmetric Laplace distribution. Im…
Mixtures of Shifted Asymmetric Laplace Distributions
Brian C. Franczak, Ryan P. Browne, Paul D. McNicholas
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…