1 citations · 1 across the 3 of their papers we have counts for
4 papers
Extending Cluster-Weighted Factor Analyzers for multivariate prediction and high-dimensional interpretability
Xiaoke Qin, Francesca Martella, Sanjeena Subedi
Cluster-weighted factor analyzers (CWFA) are a versatile class of mixture models designed to estimate the joint distribution of a random vector that includes a response variable al…
Finite Mixtures of Multivariate Poisson-Log Normal Factor Analyzers for Clustering Count Data
Andrea Payne, Anjali Silva, Steven J. Rothstein +2
A mixture of multivariate Poisson-log normal factor analyzers is introduced by imposing constraints on the covariance matrix, which resulted in flexible models for clustering purpo…
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…
Estimation of Gaussian Bi-Clusters with General Block-Diagonal Covariance Matrix and Applications
Anastasiia Livochka, Ryan Browne, Sanjeena Subedi
Bi-clustering is a technique that allows for the simultaneous clustering of observations and features in a dataset. This technique is often used in bioinformatics, text mining, and…