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2016

Conference Publication

Finding group structures in "Big Data" in healthcare research using mixture models

Ng, Shu-Kay and McLachlan, Geoffrey J. (2016). Finding group structures in "Big Data" in healthcare research using mixture models. IEEE International Conference on Bioinformatics and Biomedicine, Shenzhen, China, 15-18 December 2016. Piscataway, NJ, United States: IEE Computer Society. doi: 10.1109/BIBM.2016.7822692

Finding group structures in "Big Data" in healthcare research using mixture models

2016

Book Chapter

Mixture distributions - further developments

McLachlan, Geoffrey J. (2016). Mixture distributions - further developments. Wiley statsref: statistics reference online. (pp. 1-13) Chichester, United Kingdom: John Wiley & Sons. doi: 10.1002/9781118445112.stat00947.pub2

Mixture distributions - further developments

2016

Journal Article

A benchmark for evaluation of algorithms for identification of cellular correlates of clinical outcomes

Aghaeepour, Nima, Chattopadhyay, Pratip, Chikina, Maria, Dhaene, Tom, Van Gassen, Sofie, Kursa, Miron, Lambrecht, Bart N., Malek, Mehrnoush, McLachlan, G. J., Qian, Yu, Qiu, Peng, Saeys, Yvan, Stanton, Rick, Tong, Dong, Vens, Celine, Walkowiak, Slawomir, Wang, Kui, Finak, Greg, Gottardo, Raphael, Mosmann, Tim, Nolan, Garry P., Scheuermann, Richard H. and Brinkman, Ryan R. (2016). A benchmark for evaluation of algorithms for identification of cellular correlates of clinical outcomes. Cytometry Part A, 89 (1), 16-21. doi: 10.1002/cyto.a.22732

A benchmark for evaluation of algorithms for identification of cellular correlates of clinical outcomes

2016

Journal Article

Mixtures of spatial spline regressions for clustering and classification

Nguyen, Hien D., McLachlan, Geoffrey J. and Wood, Ian A. (2016). Mixtures of spatial spline regressions for clustering and classification. Computational Statistics and Data Analysis, 93, 76-85. doi: 10.1016/j.csda.2014.01.011

Mixtures of spatial spline regressions for clustering and classification

2016

Journal Article

Extending mixtures of factor models using the restricted multivariate skew-normal distribution

Lin, Tsung-I, McLachlan, Geoffrey J. and Lee, Sharon X. (2016). Extending mixtures of factor models using the restricted multivariate skew-normal distribution. Journal of Multivariate Analysis, 143, 398-413. doi: 10.1016/j.jmva.2015.09.025

Extending mixtures of factor models using the restricted multivariate skew-normal distribution

2016

Conference Publication

Unsupervised component-wise EM learning for finite mixtures of skew t-distributions

Lee, Sharon X. and McLachlan, Geoffrey J. (2016). Unsupervised component-wise EM learning for finite mixtures of skew t-distributions. 12th International Conference, ADMA 2016, Gold Coast, QLD, Australia, 12-15 December 2016. New York, NY, United States: Springer. doi: 10.1007/978-3-319-49586-6_49

Unsupervised component-wise EM learning for finite mixtures of skew t-distributions

2016

Conference Publication

On mixture modelling with multivariate skew distributions

Lee, Sharon X. and McLachlan, Geoffrey J. (2016). On mixture modelling with multivariate skew distributions. COMPSTAT: International Conference on Computational Statistics, Oviedo, Spain, 23-26 August 2016. The Hague, The Netherlands: The International Statistical Institute/International Association for Statistical Computing.

On mixture modelling with multivariate skew distributions

2016

Conference Publication

A simple parallel EM algorithm for statistical learning via mixture models

Lee, Sharon X., Leemaqz, Kaleb L. and McLachlan, Geoffrey J. (2016). A simple parallel EM algorithm for statistical learning via mixture models. International Conference on Digital Image Computing, Gold Coast, QLD, Australia, 30 November - 2 December,2016. Piscataway, NJ, United States: IEEE (Institute for Electrical and Electronic Engineers). doi: 10.1109/DICTA.2016.7796997

A simple parallel EM algorithm for statistical learning via mixture models

2016

Book Chapter

Application of mixture models to large datasets

Lee, Sharon X., McLachlan, Geoffrey J. and Pyne, Saumyadipta (2016). Application of mixture models to large datasets. Big data analytics: methods and applications. (pp. 57-74) edited by Saumyadipta Pyne, B. L. S. Prakasa Rao and S. B. Rao. New Delhi, India: Springer India. doi: 10.1007/978-81-322-3628-3_4

Application of mixture models to large datasets

2015

Journal Article

Application of multiple imputation for missing values in three-way three-mode multi-environment trial data

Tian, Ting, McLachlan, Geoffrey J., Dieter, Mark J. and Basford, Kaye E. (2015). Application of multiple imputation for missing values in three-way three-mode multi-environment trial data. PLoS One, 10 (12) e0144370, e0144370.1-e0144370.25. doi: 10.1371/journal.pone.0144370

Application of multiple imputation for missing values in three-way three-mode multi-environment trial data

2015

Edited Outputs

Advances in Data Analysis and Classification

Advances in Data Analysis and Classification. (2015). 9 (4)

Advances in Data Analysis and Classification

2015

Journal Article

Special issue on "New trends on model-based clustering and classification"

Ingrassia, Salvatore, McLachlan, Geoffrey J. and Govaert, Gerard (2015). Special issue on "New trends on model-based clustering and classification". Advances in Data Analysis and Classification, 9 (4), 367-369. doi: 10.1007/s11634-015-0224-8

Special issue on "New trends on model-based clustering and classification"

2015

Journal Article

Maximum likelihood estimation of Gaussian mixture models without matrix operations

Nguyen, Hien D. and McLachlan, Geoffrey J. (2015). Maximum likelihood estimation of Gaussian mixture models without matrix operations. Advances in Data Analysis and Classification, 9 (4), 371-394. doi: 10.1007/s11634-015-0209-7

Maximum likelihood estimation of Gaussian mixture models without matrix operations

2015

Book Chapter

Computation: Expectation-Maximization Algorithm

McLachlan, Geoffrey J. (2015). Computation: Expectation-Maximization Algorithm. International Encyclopedia of the Social & Behavioral Sciences: Second Edition. (pp. 469-474) Amsterdam, Netherlands: Elsevier . doi: 10.1016/B978-0-08-097086-8.42007-6

Computation: Expectation-Maximization Algorithm

2015

Book Chapter

Multivariate Analysis: Classification and Discrimination

McLachlan, Geoffrey (2015). Multivariate Analysis: Classification and Discrimination. International Encyclopedia of the Social & Behavioral Sciences: Second Edition. (pp. 116-120) Amsterdam, Netherlands: Elsevier . doi: 10.1016/B978-0-08-097086-8.42150-1

Multivariate Analysis: Classification and Discrimination

2015

Journal Article

Nature and man: the goal of bio-security in the course of rapid and inevitable human development

Pyne, Saumyadipta, Lee, Sharon X. and McLachlan, Geoffrey J. (2015). Nature and man: the goal of bio-security in the course of rapid and inevitable human development. Journal of the Indian Society of Agricultural Statistics, 69 (2), 117-125.

Nature and man: the goal of bio-security in the course of rapid and inevitable human development

2015

Journal Article

Inference on differences between classes using cluster-specific contrasts of mixed effects

Ng, Shu Kay, McLachlan, Geoffrey J., Wang, Kui, Nagymanyoki, Zoltan, Liu, Shubai and Ng, Shu-Wing (2015). Inference on differences between classes using cluster-specific contrasts of mixed effects. Biostatistics, 16 (1), 98-112. doi: 10.1093/biostatistics/kxu028

Inference on differences between classes using cluster-specific contrasts of mixed effects

2015

Book Chapter

Mixture Models in Statistics

McLachlan, Geoffrey J. (2015). Mixture Models in Statistics. International Encyclopedia of the Social & Behavioral Sciences: Second Edition. (pp. 624-628) Amsterdam, Netherlands: Elsevier . doi: 10.1016/B978-0-08-097086-8.42055-6

Mixture Models in Statistics

2014

Journal Article

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

Lin, Tsung-I, Wu, Pal H., McLachlan, Geoffrey J. and Lee, Sharon X. (2014). A robust factor analysis model using the restricted skew-t distribution. Test, 24 (3), 510-531. doi: 10.1007/s11749-014-0422-2

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

2014

Journal Article

On the number of components in a Gaussian mixture model

McLachlan, Geoffrey J. and Rathnayake, Suren (2014). On the number of components in a Gaussian mixture model. Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery, 4 (5), 341-355. doi: 10.1002/widm.1135

On the number of components in a Gaussian mixture model