14 citations · 19 across the 3 of their papers we have counts for
7 papers
On mean and/or variance mixtures of normal distributions
Sharon X. Lee, Geoffrey J. McLachlan
Parametric distributions are an important part of statistics. There is now a voluminous literature on different fascinating formulations of flexible distributions. We present a sel…
Multi-Node EM Algorithm for Finite Mixture Models
Sharon X. Lee, Geoffrey J. McLachlan, Kaleb L. Leemaqz
Finite mixture models are powerful tools for modelling and analyzing heterogeneous data. Parameter estimation is typically carried out using maximum likelihood estimation via the E…
Comment on "Hidden truncation hyperbolic distributions, finite mixtures thereof and their application for clustering" Murray, Browne, and \McNicholas
Geoffrey J. McLachlan, Sharon X. Lee
We comment on the paper of Murray, Browne, and McNicholas (2017), who proposed mixtures of skew distributions, which they termed hidden truncation hyperbolic (HTH). They recently m…
On formulations of skew factor models: skew errors versus skew factors
Sharon X. Lee, Geoffrey J. McLachlan
In the past few years, there have been a number of proposals for generalizing the factor analysis (FA) model and its mixture version (known as mixtures of factor analyzers (MFA)) u…
Mixtures of Factor Analyzers with Fundamental Skew Symmetric Distributions
Sharon X. Lee, Tsung-I Lin, Geoffrey J. McLachlan
Mixtures of factor analyzers (MFA) provide a powerful tool for modelling high-dimensional datasets. In recent years, several generalizations of MFA have been developed where the no…
A simple multithreaded implementation of the EM algorithm for mixture models
Sharon X Lee, Kaleb L Lee, Geoffrey J McLachlan
Finite mixture models have been widely used for the modelling and analysis of data from heterogeneous populations. Maximum likelihood estimation of the parameters is typically carr…