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McLachlan, G (1998) 25 years of applied statistics. Journal of Applied Statistics, 25 1: 3-22. 69   0
Ganesalingam, S. and McLachlan, G. J. (1979) A case study of two clustering methods based on maximum likelihood. Statistica Neerlandica, 33 2: 81-90. doi:10.1111/j.1467-9574.1979.tb00665.x 31   0
Sun, Mingzhu and McLachlan, Geoffrey J (2013). A common factor-analytic model for classification. In: Bioinformatics and Biomedicine (BIBM), 2013 IEEE International Conference on. IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013, Shanghai China, (19-24). 18 - 21 December 2013. doi:10.1109/BIBM.2013.6732722 55   Cited 0 times in Scopus0 0
Nikulin, Vladimir, Huang, Tian-Hsiang and McLachlan, Geoffrey J. (2010). A comparative study of two matrix factorization methods applied to the classification of gene expression rate. In: T. Park, L. Chen, L. Wong, S. Tsui, M. Ng and X. Hu, Proceedings of 2010 IEEE International Conference on Bioinformatics and Biomedicine. IEEE International Conference on Bioinformatics & Biomedicine, Hong Kong, (618-621). 18-21 December 2010. 97  
Ganesalingam, S and McLachlan, GJ (1980) A Comparison of the Mixture and Classification Approaches to Cluster-Analysis. Communications in Statistics Part A-Theory and Methods, 9 9: 923-933. doi:10.1080/03610928008827932 44   7 0
McLachlan, G (1993) A Connection Between the Logit Model, Normal Discriminant-Analysis, and Multivariate Normal Mixtures - Comment. American Statistician, 47 1: 88-88. 54   1
Jones, P. N. and McLachlan, G. J. (1990) Algorithm AS 254: maximum likelihood estimation from grouped and truncated data with finite normal mixture models. Applied Statistics - Journal of the Royal Statistical Society Series C, 39 2: 273-282. doi:10.2307/2347776 45   13 0
McLachlan, 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 73   272 Cited 300 times in Scopus300 0
Ng, SK, McLachlan, GJ, Wang, K, Jones, LBT and Ng, SW (2006) A Mixture model with random-effects components for clustering correlated gene-expression profiles. Bioinformatics, 22 14: 1745-1752. doi:10.1093/bioinformatics/btl165 970   66 Cited 72 times in Scopus72 0
McLachlan, G. J., Ng, S. K., Adams, P., McGiffin, D. C. and Galbraith, A. J. (1997) An algorithm for fitting mixtures of Gompertz distributions to censored survival data. Journal of Statistical Software, 2 7: 1-23. 39   Cited 4 times in Scopus4
McLachlan, GJ, McLaren, CE and Matthews, D (1995) An Algorithm for the Likelihood Ratio Test of One Versus 2 Components in a Normal Mixture Model Fitted to Grouped and Truncated Data. Communications in Statistics-Simulation and Computation, 24 4: 965-985. doi:10.1080/03610919508813288 36   3 0
Holt, JN and McLachlan, GJ (1979). Analysis of Some Censored Survival Data From a Large-Scale Study of Melanoma. In: Biometrics. , , (697-697). . 36   0
McLachlan, G. J., Do, K. and Ambroise, C Analyzing Microarray Gene Expression Data. New York: Wiley-Interscience, 2004. 68  
McGiffin, DC, Obrien, MF, Galbraith, AJ, McLachlan, GJ, Stafford, EG, Gardner, Mah, Pohlner, PG, Early, L and Kear, L (1993) An Analysis of Risk-Factors for Death and Mode-Specific Death After Aortic-Valve Replacement with Allograft, Xenograft, and Mechanical Valves. Journal of Thoracic and Cardiovascular Surgery, 106 5: 895-911. 38   19
McGiffin, DC, Galbraith, AJ, OBrien, MF, McLachlan, GJ, Naftel, DC, Adams, P, Reddy, S and Early, L (1997) An analysis of valve re-replacement after aortic valve replacement with biologic devices. Journal of Thoracic And Cardiovascular Surgery, 113 2: 311-318. doi:10.1016/S0022-5223(97)70328-3 176   26 Cited 28 times in Scopus28 0
Ng, 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 123   15 Cited 15 times in Scopus15 0
McLachlan, G. J. (2012). An enduring interest in classification: supervised and unsupervised. In Mohamed Medhat Gaber (Ed.), Journeys to data mining: experiences from 15 renowned researchers (pp. 147-171) Heidelberg, Germany: Springer. 66  
Ng, S. K., McLachlan, G. J. and Lee, A. H. (2006) An Incremental EM-based Learning Approach for On-Line Prediction of Hospital Resource Utilization. Artificial Intelligence In Medicine, 36 3: 257-267. doi:10.1016/j.artmed.2005.07.003 101   8 Cited 10 times in Scopus10 0
McLachlan, GJ (1980) A Note On Bias Correction in Maximum Likelihood Estimation with Logistic Discrimination. Technometrics, 22 4: 621-627. doi:10.2307/1268202 38   19 0
Quinn, BG, McLachlan, GJ and Hjort, NL (1987) A Note On the Aitkin-Rubin Approach to Hypothesis-Testing in Mixture-Models. Journal of the Royal Statistical Society Series B-Methodological, 49 3: 311-314. 44   17
McGiffin, DC, Galbraith, AJ, McLachlan, GJ, Stower, RE, Wong, ML, Stafford, EG, Gardner, Mah, Pohlner, PG and Obrien, MF (1992) Aortic-Valve Infection - Risk-Factors for Death and Recurrent Endocarditis After Aortic-Valve Replacement. Journal of Thoracic and Cardiovascular Surgery, 104 2: 511-520. 47   100
Do, K. A., McLachlan, G. J., Bean, R. W. and Wen, S. (2007) Application of gene shaving and mixture models to cluster microarray gene expression data. Cancer Informatics, 5 25-43. 130   Cited 1 times in Scopus1
Jones, LBT, Bean, R, McLachlan, G and Zhu, J (2005) Application of mixture models to detect differentially expressed genes. Intelligent Data Engineering And Automated Learning Ideal 2005, Proceedings, 3578 -: 422-431. 63   1 Cited 1 times in Scopus1
Zhao, Yun, Lee, Andy H., Yau, Kelvin K. W., Burke, Valerie and McLachlan, Geoffrey J. (2009) A score test for assessing the cured proportion in the long-term survivor mixture model. Statistics In Medicine, 28 27: 3454-3466. doi:10.1002/sim.3696 63   5 Cited 4 times in Scopus4 0
Xiang, L., Lee, A. H., Yau, K. K. W. and McLachlan, G. J. (2007) A Score Test for Overdispersion in Zero-Inflated Poisson Mixed Regression Model. Statistics in Medicine, 26 7: 1608-1622. doi:10.1002/sim.2616 171   26 Cited 27 times in Scopus27 0
Xiang, Liming, Lee, Andy H., Yau, Kelvin K. W. and McLachlan, Geoffrey J. (2006) A Score Test for Zero-Inflation in Correlated Count Data. Statistics In Medicine, 25 10: 1660-1671. doi:10.1002/sim.2308 118   20 Cited 21 times in Scopus21 0
McLachlan, GJ, Bean, RW and Jones, LBT (2006) A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays. Bioinformatics, 22 13: 1608-1615. doi:10.1093/bioinformatics/btl148 64   73 Cited 79 times in Scopus79 0
Zhao, Yun, Lee, Andy H., Yau, Kelvin K.W. and McLachlan, Geoffrey J. (2011) Assessing the adequacy of Weibull survival models: a simulated envelope approach. Journal of Applied Statistics, 38 10: 2089-2097. doi:10.1080/02664763.2010.545115 69   0 Cited 0 times in Scopus0 0
McLachlan, GJ (1986) Assessing the Performance of An Allocation Rule. Computers & Mathematics with Applications-Part a, 12 2: 261-272. doi:10.1016/0898-1221(86)90079-9 33   16 0
McLachla.GJ (1974) Asymptotic Distributions of Conditional Error Rate and Risk in Discriminant-Analysis. Biometrika, 61 1: 131-135. doi:10.1093/biomet/61.1.131 38   16 0
Lawoko, Cro and McLachlan, GJ (1986) Asymptotic Error Rates of the W-Statistics and Z-Statistics When the Training Observations Are Dependent. Pattern Recognition, 19 6: 467-471. doi:10.1016/0031-3203(86)90045-2 35   4 0
McLachla.GJ (1972) Asymptotic Expansion for Variance of Errors of Misclassification of Linear Discriminant Function. Australian Journal of Statistics, 14 1: 68-72. 32   12
McLachla.GJ (1973) Asymptotic Expansion of Expectation of Estimated Error Rate in Discriminant-Analysis. Australian Journal of Statistics, 15 3: 210-214. 38   16
Nguyen, Hien D. and McLachlan, Geoffrey J. (2014). Asymptotic inference for hidden process regression models. In: 2014 IEEE Workshop on Statistical Signal Processing, SSP 2014. 2014 IEEE Workshop on Statistical Signal Processing (SSP 2014), Gold Coast, Australia, (256-259). 29 June - 2 July 2014. doi:10.1109/SSP.2014.6884624 26   Cited 0 times in Scopus0 0
McLachlan, GJ and Scot, D (1995) Asymptotic Relative Efficiency of the Linear Discriminant Function Under Partial Nonrandom Classification of the Training Data. Journal of Statistical Computation and Simulation, 52 4: 415-426. doi:10.1080/00949659508811689 36   1 0
McLachla.GJ (1972) Asymptotic Results for Discriminant Analysis When Initial Samples Are Misclassified. Technometrics, 14 2: 415-&. doi:10.2307/1267432 23   20 0
McLachla.GJ (1974) Asymptotic Unbiased Technique for Estimating Error Rates in Discriminant-Analysis. Biometrics, 30 2: 239-249. doi:10.2307/2529646 41   38 0
Suarez, E., Sariol, C. A., Burguete, A. and McLachlan, G. J. (2007) A tutorial in genetic epidemiology and some considerations in statistical modeling. Puerto Rico Health Sciences Journal, 26 4: 401-421. 124   Cited 3 times in Scopus3
Tang, Liangdan, Yang, Junzheng, Ng, Shu-Kay, Rodriguez, Noah, Choi, Pui-Wah, Vitonis, Allison, Wang, Kui, McLachlan, Geoffrey J., Caiazzo, Robert J., Liu, Brian C.-S., Welch, Brian C.-S., Cramer, Daniel W., Berkowitz, Ross S. and Ng, Shu-Wing (2010) Autoantibody profiling to identify biomarkers of key pathogenic pathways in mucinous ovarian cancer. European Journal of Cancer, 46 1: 170-179. doi:10.1016/j.ejca.2009.10.003 60   16 Cited 19 times in Scopus19 0
Pyne, S., Hu, X., Wang, K., Rossin, E., Lin, T.-I., Maier, L. M., Baecher-Allan, C., McLachlan, G. J., Tamayo, P., Hafler, D. A., De Jager, P. L. and Mesirow, J. P. (2009) Automated high-dimensional flow cytometric data analysis. Proceedings of the National Academy of Sciences of the United States of America, 106 21: 8519-8524. doi:10.1073/pnas.0903028106 78   99 Cited 98 times in Scopus98 0
Pyne, Saumyadipta, Hu, Xinli, Wang, Kui, Rossin, Elizabeth, Lin, Tsung-I, Maier, Lisa, Baecher-Allan, Clare, McLachlan, Geoffrey, Tamayo, Pablo, Hafler, David, De Jager, Philip and Mesirov, Jill (2010). Automated high-dimensional flow cytometric data analysis. In: Bonnie Berger, Research in Computational Molecular Biology: 14th Annual International Conference, RECOMB 2010: Proceedings. 14th Annual International Conference on Research in Computational Molecular Biology, Lisbon, Portugal, (577-577). 25-28 April 2010. doi:10.1007/978-3-642-12683-3_41 61   1 0
Nikulin, V, Huang, TH, Ng, SK, Rathnayake, SI and McLachlan, GJ (2011) A very fast algorithm for matrix factorization. Statistics and Probability Letters, 81 7: 773-782. doi:10.1016/j.spl.2011.02.001 74   6 Cited 9 times in Scopus9 0
McLachlan, GJ (1978). Bias Associated with Maximum Likelihood Estimation of Multivariate Logistic Risk Function. In: Biometrics. , , (172-172). . 43   0
Lawoko, Cro and McLachlan, GJ (1989) Bias Associated with the Discriminant-Analysis Approach to the Estimation of Mixing Proportions. Pattern Recognition, 22 6: 763-766. doi:10.1016/0031-3203(89)90012-5 34   3 0
Byth, K and McLachlan, GJ (1978) Biases Associated with Maximum Likelihood Methods of Estimation of Multivariate Logistic Risk Function. Communications in Statistics Part A-Theory and Methods, 7 9: 877-890. doi:10.1080/03610927808827679 41   8 0
McLachlan, GJ (1976) Bias of Apparent Error Rate in Discriminant-Analysis. Biometrika, 63 2: 239-244. doi:10.2307/2335615 37   27 0
McLaren, C. E., Gordeuk, V. R., Chen, W. -P., Barton, J. C., Action, R. T., Speechley, M., Castro, O., Adams, P. C., Snively, B. M., Harris, E. L., Reboussin, D. M., McLachlan, G. J. and Bean, R. (2008) Bivariate mixture modeling of transferrin saturation and serum ferritin concentration in Asians, African Americans, Hispanics, and whites in the Hemochromatosis and Iron Overload Screening (HEIRS) Study. Translational Research, 151 2: 97-109. doi:10.1016/j.trsl.2007.10.002 90   2 Cited 2 times in Scopus2 0
Caprani, C. C., O'Brien, E. J. and McLachlan, G. J. (2008) Characteristic Traffic Load Effects from a Mixture of Loading Events on Short to Medium Span Bridges. Structural Safety, 30 3: 394-404. doi:10.1016/j.strusafe.2006.11.006 69   12 Cited 18 times in Scopus18 0
Nikulin, Vladimir, Huang, Tian-Hsiang and McLachlan, Geoffrey J. (2011) Classification of high-dimensional microarray data with a two-step procedure via a Wilcoxon criterion and multilayer perceptron. International Journal of Computational Intelligence and Applications, 10 1: 1-14. doi:10.1142/S1469026811002969 56   Cited 0 times in Scopus0 0
Nikulin, Vladimir and McLachlan, Geoffrey J. (2009). Classification of imbalanced marketing data with balanced random sets. In: Gideon Dror, Marc BoullĀ“e, Isabelle Guyon, Vincent Lemaire and David Vogel, Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics. AISTATS 2009, Clearwater Beach, FL, United States, (89-100). 16-18 April 2009. 86 2

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