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2005 Journal Article Use of the EM algorithm to detect QTL affecting multiple-traits in an across half-sib family analysisKerr, R. J., McLachlan, G. J. and Henshall, J. M. (2005). Use of the EM algorithm to detect QTL affecting multiple-traits in an across half-sib family analysis. Genetics Selection Evolution, 37 (1), 83-103. doi: 10.1051/gse:2004037 |
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2004 Journal Article Modelling the Distribution of Ischaemic Stroke-Specific Survival Time Using an EM-based Mixture Approach with Random Effects AdjustmentNg, S. K., McLachlan, G. J., Yau, K. K. W. and Lee, A. H. (2004). Modelling the Distribution of Ischaemic Stroke-Specific Survival Time Using an EM-based Mixture Approach with Random Effects Adjustment. Statistics In Medicine, 23 (17), 2729-2744. doi: 10.1002/sim.1840 |
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2004 Journal Article Speeding up the EM algorithm for mixture model-based segmentation of magnetic resonance imagesNg, Shu-Kay and McLachlan, Geoffrey J. (2004). Speeding up the EM algorithm for mixture model-based segmentation of magnetic resonance images. Pattern Recognition, 37 (8), 1573-1589. doi: 10.1016/j.patcog.2004.02.012 |
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2004 Journal Article Using the EM Algorithm to Train Neural Networks: Misconceptions and a New Algorithm for Multiclass ClassificationNg, S. K. and McLachlan, G. J. (2004). Using the EM Algorithm to Train Neural Networks: Misconceptions and a New Algorithm for Multiclass Classification. IEEE Transactions on Neural Networks, 15 (3), 738-749. doi: 10.1109/TNN.2004.826217 |
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2004 Journal Article Clustering objects on subsets of attributes - DiscussionHand, DJ, Glasbey, C, Husmeier, D, Gower, JC, van Houwelingen, HC, Bugrien, JB, Nason, G, Critchley, F, Hoff, PD, McLachlan, GJ and Bean, RW (2004). Clustering objects on subsets of attributes - Discussion. Journal of The Royal Statistical Society Series B-statistical Methodology, 66 (4), 839-849. |
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2004 Journal Article Mixture modelling for cluster analysisMcLachlan, G. J. and Chang, S. U. (2004). Mixture modelling for cluster analysis. Statistical Methods In Medical Research, 13 (5), 347-361. doi: 10.1191/0962280204sm372ra |
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2004 Journal Article On a resampling approach for tests on the number of clusters with mixture model-based clustering of tissue samplesMcLachlan, GJ and Khan, N (2004). On a resampling approach for tests on the number of clusters with mixture model-based clustering of tissue samples. Journal of Multivariate Analysis, 90 (1), 90-105. doi: 10.1016/j.jmva.2004.02.002 |
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2003 Journal Article Model-based clustering in gene expression microarrays: an application to breast cancer dataMar, J. C. and McLachlan, G. J. (2003). Model-based clustering in gene expression microarrays: an application to breast cancer data. International Journal of Software Engineering And Knowledge Engineering, 13 (6), 579-592. doi: 10.1142/S0218194003001482 |
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2003 Journal Article Model-based clustering in gene expression microarrays: an application to breast cancer dataMar, J.C. and McLachlan, G.J. (2003). Model-based clustering in gene expression microarrays: an application to breast cancer data. International Journal of Software Engineering and Knowledge Engineering, 13 (6), 579-592. doi: 10.1142/S0218194003001482 |
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2003 Journal Article An EM-based Semi-Parametric Mixture Model Approach to the Regression Analysis of Competing-Risks DataNg, S. K. and McLachlan, G. J. (2003). An EM-based Semi-Parametric Mixture Model Approach to the Regression Analysis of Competing-Risks Data. Statistics In Medicine, 22 (7), 1097-1111. doi: 10.1002/sim.1371 |
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2003 Journal Article On the Choice of the Number of Blocks with the Incremental EM Algorithm for the Fitting of Normal MixturesNg, S. K. and McLachlan, G. J. (2003). On the Choice of the Number of Blocks with the Incremental EM Algorithm for the Fitting of Normal Mixtures. Statistics And Computing, 13 (1), 45-55. doi: 10.1023/A:1021987710829 |
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2003 Journal Article Modelling High-Dimensional Data by Mixtures of Factor AnalyzersMcLachlan, G. J., Peel, D. and Bean, R. W. (2003). Modelling High-Dimensional Data by Mixtures of Factor Analyzers. Computational Statistics & Data Analysis, 41 (3-4), 379-388. doi: 10.1016/S0167-9473(02)00183-4 |
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2003 Journal Article On some variants of the EM algorithm for the fitting of finite mixture modelsNg, A.S. K. and McLachlan, G. J. (2003). On some variants of the EM algorithm for the fitting of finite mixture models. Austrian Journal of Statistics, 32 (1 & 2), 143-161. |
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2002 Journal Article Selection bias in gene extraction on the basis of microarray gene-expression dataAmbroise, Christophe and McLachlan, Geoffrey J. (2002). Selection bias in gene extraction on the basis of microarray gene-expression data. Proceedings of the National Academy of Sciences of the United States of America, 99 (10), 6562-6566. doi: 10.1073/pnas.102102699 |
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2002 Journal Article Maximum Likelihood Estimation of Mixture Densities for Binned and Truncated Multivariate DataCadez, I. V., Smyth, P., McLachlan, G. J. and McLaren, C. E. (2002). Maximum Likelihood Estimation of Mixture Densities for Binned and Truncated Multivariate Data. Machine Learning, 47 (1), 7-34. doi: 10.1023/A:1013679611503 |
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2002 Journal Article Influence of patient age and implantation technique on the probability of re-replacement of the homograft aortic valveNg, S. K., O'Brien, M. F., Harrocks, S. N. and McLachlan, G. J. (2002). Influence of patient age and implantation technique on the probability of re-replacement of the homograft aortic valve. Journal of Heart Valve Disease, 11 (2), 217-223. |
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2002 Journal Article Nearest-neighbor variance estimation (NNVE): Robust covariance estimation via nearest-neighbor cleaning - CommentMcLachlan, G. J. and Hamaty, K. L. (2002). Nearest-neighbor variance estimation (NNVE): Robust covariance estimation via nearest-neighbor cleaning - Comment. Journal of The American Statistical Association, 97 (460), 1009-1011. doi: 10.1198/016214502388618807 |
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2002 Journal Article A mixture model-based approach to the clustering of microarray expression dataMcLachlan, GJ, Bean, RW and Peel, D (2002). A mixture model-based approach to the clustering of microarray expression data. Bioinformatics, 18 (3), 413-422. doi: 10.1093/bioinformatics/18.3.413 |
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2001 Journal Article MRI based diffusion and perfusion predictive model to estimate stroke evolutionRose, Stephen E., Chalk, Jonathan B., Griffin, Mark P., Janke, Andrew L., Chen, Fang, Mclachlan, Geoffrey J., Peel, David, Zelaya, Fernando O., Markus, Hugh S., Jones, Derek K., Simmons, Andrew, O'Sullivan, Michael, Jarosz, Jo M., Strugnell, Wendy and Doddrell, David M. (2001). MRI based diffusion and perfusion predictive model to estimate stroke evolution. Magnetic Resonance Imaging, 19 (8), 1043-1053. doi: 10.1016/S0730-725X(01)00435-0 |
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2001 Journal Article Letter to the editorMcLachlan, G. J. (2001). Letter to the editor. Journal of Agricultural, Biological, and Environmental Statistics, 6 (2), 302-304. doi: 10.1198/108571101750524797 |
