33 citations · 77 across the 8 of their papers we have counts for
8 papers
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…
Robust Model-Based Clustering of Voting Records
Yang Tang, Paul D. McNicholas, Antonio Punzo
We explore the possibility of discovering extreme voting patterns in the U.S. Congressional voting records by drawing ideas from the mixture of contaminated normal distributions. A…
Flexible High-Dimensional Unsupervised Learning with Missing Data
Yuhong Wei, Yang Tang, Paul D. McNicholas
The mixture of factor analyzers (MFA) model is a famous mixture model-based approach for unsupervised learning with high-dimensional data. It can be useful, inter alia, in situatio…
Clustering Airbnb Reviews
Yang Tang, Paul D. McNicholas
In the last decade, online customer reviews increasingly exert influence on consumers' decision when booking accommodation online. The renewal importance to the concept of word-of…
Flexible Clustering for High-Dimensional Data via Mixtures of Joint Generalized Hyperbolic Models
Yang Tang, Ryan P. Browne, Paul D. McNicholas
A mixture of joint generalized hyperbolic distributions (MJGHD) is introduced for asymmetric clustering for high-dimensional data. The MJGHD approach takes into account the cluster…
Extending Growth Mixture Models Using Continuous Non-Elliptical Distributions
Yuhong Wei, Yang Tang, Emilie Shireman +2
Growth mixture models (GMMs) incorporate both conventional random effects growth modeling and latent trajectory classes as in finite mixture modeling; therefore, they offer a way t…
Mixtures of Generalized Hyperbolic Distributions and Mixtures of Skew-t Distributions for Model-Based Clustering with Incomplete Data
Yuhong Wei, Yang Tang, Paul D. McNicholas
Robust clustering from incomplete data is an important topic because, in many practical situations, real data sets are heavy-tailed, asymmetric, and/or have arbitrary patterns of m…
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…