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03/24/2023
Tackling the infinite likelihood problem when fitting mixtures of shifted asymmetric Laplace distributions
Mixtures of shifted asymmetric Laplace distributions were introduced as ...
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02/08/2023
Estimation of Gaussian Bi-Clusters with General Block-Diagonal Covariance Matrix and Applications
Bi-clustering is a technique that allows for the simultaneous clustering...
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01/06/2021
Logistic Normal Multinomial Factor Analyzers for Clustering Microbiome Data
The human microbiome plays an important role in human health and disease...
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11/12/2020
Clustering microbiome data using mixtures of logistic normal multinomial models
Discrete data such as counts of microbiome taxa resulting from next-gene...
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09/10/2020
A Family of Mixture Models for Biclustering
Biclustering is used for simultaneous clustering of the observations and...
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05/11/2020
Infinite mixtures of multivariate normal-inverse Gaussian distributions for clustering of skewed data
Mixtures of multivariate normal inverse Gaussian (MNIG) distributions ca...
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05/06/2020
A Bayesian approach for clustering skewed data using mixtures of multivariate normal-inverse Gaussian distributions
Non-Gaussian mixture models are gaining increasing attention for mixture...
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04/15/2020
A parsimonious family of multivariate Poisson-lognormal distributions for clustering multivariate count data
Multivariate count data are commonly encountered through high-throughput...
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07/22/2018
Finite mixtures of matrix-variate Poisson-log normal distributions for three-way count data
Three-way data structures, characterized by three entities, the units, t...
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11/30/2017
A Multivariate Poisson-Log Normal Mixture Model for Clustering Transcriptome Sequencing Data
High-dimensional data of discrete and skewed nature is commonly encounte...
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09/07/2013
Variational Bayes Approximations for Clustering via Mixtures of Normal Inverse Gaussian Distributions
Parameter estimation for model-based clustering using a finite mixture o...
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06/25/2013
Constrained Optimization for a Subset of the Gaussian Parsimonious Clustering Models
The expectation-maximization (EM) algorithm is an iterative method for f...
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06/23/2013
