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- Publications
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Finite mixtures of multivariate skew t-distributions: some recent and new results

- S. Lee, G. J. McLachlan
- Computer Science, Mathematics
- Stat. Comput.
- 1 March 2014

Finite mixtures of multivariate skew t (MST) distributions have proven to be useful in modelling heterogeneous data with asymmetric and heavy tail behaviour. Recently, they have been exploited as an… Expand

On mixtures of skew normal and skew $$t$$-distributions

- S. Lee, G. J. McLachlan
- Mathematics, Computer Science
- Adv. Data Anal. Classif.
- 15 November 2012

Finite mixtures of skew distributions have emerged as an effective tool in modelling heterogeneous data with asymmetric features. With various proposals appearing rapidly in the recent years, which… Expand

Model-based clustering and classification with non-normal mixture distributions

- S. Lee, G. J. McLachlan
- Computer Science, Mathematics
- Stat. Methods Appl.
- 31 July 2013

Non-normal mixture distributions have received increasing attention in recent years. Finite mixtures of multivariate skew-symmetric distributions, in particular, the skew normal and skew… Expand

EMMIXuskew: An R Package for Fitting Mixtures of Multivariate Skew t Distributions via the EM Algorithm

- S. Lee, G. J. McLachlan
- Mathematics
- 22 November 2012

This paper describes an algorithm for fitting finite mixtures of unrestricted Multivariate Skew t (FM-uMST) distributions. The package EMMIXuskew implements a closed-form expectation-maximization… Expand

On the fitting of mixtures of multivariate skew t-distributions via the EM algorithm

- S. Lee, G. McLachlan
- Mathematics
- 22 September 2011

We show how the expectation-maximization (EM) algorithm can be applied exactly for the fitting of mixtures of general multivariate skew t (MST) distributions, eliminating the need for computationally… Expand

Finite mixtures of canonical fundamental skew t-distributions - The unification of the restricted and unrestricted skew t-mixture models

- S. Lee, G. J. McLachlan
- Computer Science, Mathematics
- Stat. Comput.
- 4 May 2014

This paper introduces a finite mixture of canonical fundamental skew t (CFUST) distributions for a model-based approach to clustering where the clusters are asymmetric and possibly long-tailed (in:… Expand

Finite mixtures of canonical fundamental skew $$t$$t-distributions

- S. Lee, G. J. McLachlan
- Mathematics
- 4 May 2014

This paper introduces a finite mixture of canonical fundamental skew $$t$$t (CFUST) distributions for a model-based approach to clustering where the clusters are asymmetric and possibly long-tailed… Expand

The skew-t factor analysis model

- Tsung-I Lin, P. H. Wu, G. J. McLachlan, S. Lee
- Mathematics
- 20 October 2013

Factor analysis is a classical data reduction technique that seeks a potentially lower number of unobserved variables that can account for the correlations among the observed variables. This paper… Expand

Joint Modeling and Registration of Cell Populations in Cohorts of High-Dimensional Flow Cytometric Data

- S. Pyne, S. Lee, +10 authors G. J. McLachlan
- Medicine, Mathematics
- PloS one
- 31 May 2013

In biomedical applications, an experimenter encounters different potential sources of variation in data such as individual samples, multiple experimental conditions, and multivariate responses of a… Expand

A robust factor analysis model using the restricted skew-$$t$$t distribution

- Tsung-I Lin, P. H. Wu, G. J. McLachlan, S. Lee
- Mathematics
- 1 September 2015

Factor analysis is a classical data-reduction technique that seeks a potentially lower number of unobserved variables that can account for the correlations among the observed variables. This paper… Expand