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20142019
most citedMixtures of Generalized Hyperbolic Distributions and Mixtures of Skew-t Distributions for Model-Based Clustering with Incomplete Data

33 citations · 77 across the 8 of their papers we have counts for

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Showing 2017Show all

5 papers · 1 filter

stat.CO2017★ 1 cited

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…

stat.AP2017

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…

stat.ME2017★ 12 cited

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…

stat.ME2017★ 7 cited

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…

stat.ME2017★ 33 cited

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…