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2025 Journal Article Towards millimetre-wave spectroscopy of human blood using an open-ended waveguideGonzales, Wilbert J. Villena, Lee, Sharon X., Flower, Robert and Abbosh, Amin (2025). Towards millimetre-wave spectroscopy of human blood using an open-ended waveguide. Measurement, 240 115552, 115552. doi: 10.1016/j.measurement.2024.115552 |
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2024 Journal Article An overview of skew distributions in model-based clusteringLee, Sharon X. and McLachlan, Geoffrey J. (2024). An overview of skew distributions in model-based clustering. Science Talks, 9 100298, 100298. doi: 10.1016/j.sctalk.2024.100298 |
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2023 Journal Article Robust clustering based on finite mixture of multivariate fragmental distributionsMaleki, Mohsen, McLachlan, Geoffrey J. and Lee, Sharon X. (2023). Robust clustering based on finite mixture of multivariate fragmental distributions. Statistical Modelling, 23 (3), 247-272. doi: 10.1177/1471082X211048660 |
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2022 Journal Article A Festschrift for Geoff McLachlanNguyen, Hien, Lee, Sharon and Forbes, Florence (2022). A Festschrift for Geoff McLachlan. Australian and New Zealand Journal of Statistics, 64 (2), 111-116. doi: 10.1111/anzs.12372 |
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2022 Journal Article An overview of skew distributions in model-based clusteringLee, Sharon X. and McLachlan, Geoffrey J. (2022). An overview of skew distributions in model-based clustering. Journal of Multivariate Analysis, 188 104853, 1-14. doi: 10.1016/j.jmva.2021.104853 |
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2021 Journal Article Multi‐node expectation–maximization algorithm for finite mixture modelsLee, Sharon X., McLachlan, Geoffrey J. and Leemaqz, Kaleb L. (2021). Multi‐node expectation–maximization algorithm for finite mixture models. Statistical Analysis and Data Mining: The ASA Data Science Journal, 14 (4) sam.11529, 297-304. doi: 10.1002/sam.11529 |
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2021 Book Chapter Automated gating and dimension reduction of high-dimensional cytometry dataLee, Sharon X., McLachlan, Geoffrey J. and Pyne, Saumyadipta (2021). Automated gating and dimension reduction of high-dimensional cytometry data. Mathematical, computational and experimental T cell immunology. (pp. 281-294) edited by Carmen Molina-París and Grant Lythe . Cham, Switzerland: Springer. doi: 10.1007/978-3-030-57204-4_16 |
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2021 Conference Publication On Mean And/or Variance Mixtures of Normal DistributionsLee, Sharon X. and McLachlan, Geoffrey J. (2021). On Mean And/or Variance Mixtures of Normal Distributions. 12th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society (CLADAG 2019), Cassino, Italy, 11–13 September 2019. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-69944-4_13 |
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2020 Journal Article Mixtures of factor analyzers with scale mixtures of fundamental skew normal distributionsLee, Sharon X., Lin, Tsung-I and McLachlan, Geoffrey J. (2020). Mixtures of factor analyzers with scale mixtures of fundamental skew normal distributions. Advances in Data Analysis and Classification, 15 (2), 481-512. doi: 10.1007/s11634-020-00420-9 |
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2020 Conference Publication Modelling asset return using multivariate asymmetric mixture models with applications to estimation of Value-at-RiskLee, Sharon X. and McLachlan, Geoffrey J. (2020). Modelling asset return using multivariate asymmetric mixture models with applications to estimation of Value-at-Risk. 20th International Congress on Modelling and Simulation - Adapting to Change: The Multiple Roles of Modelling, MODSIM 2013 , Adelaide, SA, Australia, 1 - 6 December 2013. Modelling and Simulation Society of Australia and New Zealand Inc. (MSSANZ). |
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2019 Journal Article Foreword to the Special Issue on Natural Resource MathematicsHolden, Matthew H., Lee, Sharon and Yang, Wen-Hsi (2019). Foreword to the Special Issue on Natural Resource Mathematics. Environmental Modeling and Assessment, 24 (4), 365-367. doi: 10.1007/s10666-019-09677-7 |
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2019 Conference Publication PPEM: privacy-preserving EM learning for mixture modelsLee, Sharon X., Leemaqz, Kaleb L. and McLachlan, Geoffrey J. (2019). PPEM: privacy-preserving EM learning for mixture models. 8th International Conference on Applications and Techniques in Information Security, ATIS 2017, Auckland, New Zealand, 6-7 July 2017. Oxford, United Kingdom: John Wiley & Sons. doi: 10.1002/cpe.5208 |
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2019 Journal Article Finite mixture modelsMcLachlan, Geoffrey J., Lee, Sharon X. and Rathnayake, Suren I. (2019). Finite mixture models. Annual Review of Statistics and Its Application, 6 (1), 355-378. doi: 10.1146/annurev-statistics-031017-100325 |
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2019 Conference Publication Flexible modelling via multivariate skew distributionsMcLachlan, Geoffrey J. and Lee, Sharon X. (2019). Flexible modelling via multivariate skew distributions. Research School on Statistics and Data Science (RSSDS 2019), Melbourne, VIC, Australia, 24–26 July 2019. Singapore, Singapore: Springer Singapore. doi: 10.1007/978-981-15-1960-4_4 |
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2019 Journal Article Skew-normal Bayesian spatial heterogeneity panel data modelsFarzammehr, Mohadeseh Alsadat, Zadkarami, Mohammad Reza, McLachlan, Geoffrey J. and Lee, Sharon X. (2019). Skew-normal Bayesian spatial heterogeneity panel data models. Journal of Applied Statistics, 47 (5), 1-23. doi: 10.1080/02664763.2019.1657812 |
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2019 Conference Publication CytoFA: automated gating of mass cytometry data via robust skew factor analzyersLee, Sharon X. (2019). CytoFA: automated gating of mass cytometry data via robust skew factor analzyers. 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2019), Macau, China, 14-17 April 2019. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-16148-4_40 |
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2018 Journal Article A Block EM Algorithm for Multivariate Skew Normal and Skew t-Mixture ModelsLee, Sharon X., Leemaqz, Kaleb L. and McLachlan, Geoffrey J. (2018). A Block EM Algorithm for Multivariate Skew Normal and Skew t-Mixture Models. IEEE Transactions on Neural Networks and Learning Systems, 29 (99) 8310916, 1-11. doi: 10.1109/TNNLS.2018.2805317 |
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2018 Journal Article EMMIXcskew: an R package for the fitting of a mixture of canonical fundamental skew t-distributionsLee, Sharon X. and McLachlan, Geoffrey J. (2018). EMMIXcskew: an R package for the fitting of a mixture of canonical fundamental skew t-distributions. Journal of Statistical Software, 83 (3). doi: 10.18637/jss.v083.i03 |
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2018 Book Chapter Risk measures based on multivariate skew normal and skew t-mixture modelsLee, Sharon X. and McLachlan, Geoffrey J. (2018). Risk measures based on multivariate skew normal and skew t-mixture models. Asymmetric dependence in finance: diversification, correlation and portfolio management in market downturns. (pp. 152-168) edited by Jamie Alcock and Stephen Satchell. Chichester, West Sussex, United Kingdom: John Wiley & Sons. doi: 10.1002/9781119288992.ch7 |
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2017 Journal Article Finite mixture models in biostatisticsLee, Sharon X., Ng, Shu-Kay and McLachlan, Geoffrey J. (2017). Finite mixture models in biostatistics. Handbook of Statistics, 36, 75-102. |
