190 citations · 1.3k across the 74 of their papers we have counts for
9 papers · 2 filters
Robust Clustering in Regression Analysis via the Contaminated Gaussian Cluster-Weighted Model
Antonio Punzo, Paul D. McNicholas
The Gaussian cluster-weighted model (CWM) is a mixture of regression models with random covariates that allows for flexible clustering of a random vector composed of response varia…
High-dimensional unsupervised classification via parsimonious contaminated mixtures
Antonio Punzo, Martin Blostein, Paul D. McNicholas
The contaminated Gaussian distribution represents a simple heavy-tailed elliptical generalization of the Gaussian distribution; unlike the often-considered t-distribution, it also…
An Adaptive LASSO-Penalized BIC
Sakyajit Bhattacharya, Paul D. McNicholas
Mixture models are becoming a popular tool for the clustering and classification of high-dimensional data. In such high dimensional applications, model selection is problematic. Th…
Modelling Receiver Operating Characteristic Curves Using Gaussian Mixtures
Amay Cheam, Paul D. McNicholas
The receiver operating characteristic curve is widely applied in measuring the performance of diagnostic tests. Many direct and indirect approaches have been proposed for modelling…
Hypothesis Testing for Parsimonious Gaussian Mixture Models
Antonio Punzo, Ryan P. Browne, Paul D. McNicholas
Gaussian mixture models with eigen-decomposed covariance structures make up the most popular family of mixture models for clustering and classification, i.e., the Gaussian parsimon…
Model Based Clustering of High-Dimensional Binary Data
Yang Tang, Ryan P. Browne, Paul D. McNicholas
We propose a mixture of latent trait models with common slope parameters (MCLT) for model-based clustering of high-dimensional binary data, a data type for which few established me…