On Using Principal Components before Separating a Mixture of Two Multivariate Normal Distributions

Citations

Cited by:

1. Michael C. Thrun & Alfred Ultsch, 2021. "Using Projection-Based Clustering to Find Distance- and Density-Based Clusters in High-Dimensional Data," Journal of Classification, Springer;The Classification Society, vol. 38(2), pages 280-312, July.
2. Edward J. Bedrick, 2020. "Data reduction prior to inference: Are there consequences of comparing groups using a t‐test based on principal component scores?," Biometrics, The International Biometric Society, vol. 76(2), pages 508-517, June.
3. Wang, Zihan & Daeipour, Mohamad & Xu, Hongyi, 2023. "Quantification and propagation of Aleatoric uncertainties in topological structures," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
4. Robert Kapłon, 2006. "A retrospective review of categorical data analysis – theory and marketing practice," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 16(1), pages 55-72.
5. Andrews, Jeffrey L., 2018. "Addressing overfitting and underfitting in Gaussian model-based clustering," Computational Statistics & Data Analysis, Elsevier, vol. 127(C), pages 160-171.
6. Douglas Steinley & Lawrence Hubert, 2008. "Order-Constrained Solutions in K-Means Clustering: Even Better Than Being Globally Optimal," Psychometrika, Springer;The Psychometric Society, vol. 73(4), pages 647-664, December.
7. Heungsun Hwang & Hec Montréal & William Dillon & Yoshio Takane, 2006. "An Extension of Multiple Correspondence Analysis for Identifying Heterogeneous Subgroups of Respondents," Psychometrika, Springer;The Psychometric Society, vol. 71(1), pages 161-171, March.
8. Cappozzo, Andrea & Greselin, Francesca & Murphy, Thomas Brendan, 2021. "Robust variable selection for model-based learning in presence of adulteration," Computational Statistics & Data Analysis, Elsevier, vol. 158(C).
9. Roberto Rocci & Maurizio Vichi & Monia Ranalli, 2025. "Mixture models for simultaneous classification and reduction of three-way data," Computational Statistics, Springer, vol. 40(1), pages 469-507, January.
10. Bouveyron, Charles & Brunet-Saumard, Camille, 2014. "Model-based clustering of high-dimensional data: A review," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 52-78.
11. Ahlquist, John S. & Breunig, Christian, 2009. "Country clustering in comparative political economy," MPIfG Discussion Paper 09/5, Max Planck Institute for the Study of Societies.
12. McLachlan, G. J. & Peel, D. & Bean, R. W., 2003. "Modelling high-dimensional data by mixtures of factor analyzers," Computational Statistics & Data Analysis, Elsevier, vol. 41(3-4), pages 379-388, January.
13. Liang, Faming, 2007. "Use of SVD-based probit transformation in clustering gene expression profiles," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6355-6366, August.
14. Bouveyron, Charles & Brunet, Camille, 2012. "Theoretical and practical considerations on the convergence properties of the Fisher-EM algorithm," Journal of Multivariate Analysis, Elsevier, vol. 109(C), pages 29-41.
15. Yoshikazu Terada, 2015. "Strong consistency of factorial $$K$$ K -means clustering," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(2), pages 335-357, April.
16. Banerjee, Trambak & Mukherjee, Gourab & Radchenko, Peter, 2017. "Feature screening in large scale cluster analysis," Journal of Multivariate Analysis, Elsevier, vol. 161(C), pages 191-212.
17. Floriello, Davide & Vitelli, Valeria, 2017. "Sparse clustering of functional data," Journal of Multivariate Analysis, Elsevier, vol. 154(C), pages 1-18.
18. Zhiliang Ma & Adam Cardinal-Stakenas & Youngser Park & Michael Trosset & Carey Priebe, 2010. "Dimensionality Reduction on the Cartesian Product of Embeddings of Multiple Dissimilarity Matrices," Journal of Classification, Springer;The Classification Society, vol. 27(3), pages 307-321, November.
19. Laura Anderlucci & Francesca Fortunato & Angela Montanari, 2022. "High-Dimensional Clustering via Random Projections," Journal of Classification, Springer;The Classification Society, vol. 39(1), pages 191-216, March.
20. A. Penttinen & W. Krzanowski & J. Kettenring & F. Rohlf & William Day & B. Weir & John Kececioglu & N. Ohsumi & Peter Willett, 1993. "Book reviews," Journal of Classification, Springer;The Classification Society, vol. 10(1), pages 125-156, January.
21. Lazhar Labiod & Mohamed Nadif, 2021. "Efficient regularized spectral data embedding," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 15(1), pages 99-119, March.
22. Douglas Steinley, 2009. "F. Murtagh (2005). Correspondence analysis and data coding with Java and R. 230 pp., US$76.00. ISBN 1584885289," Psychometrika, Springer;The Psychometric Society, vol. 74(1), pages 181-183, March.
23. Dirk Depril & Iven Mechelen & Tom Wilderjans, 2012. "Lowdimensional Additive Overlapping Clustering," Journal of Classification, Springer;The Classification Society, vol. 29(3), pages 297-320, October.
24. Yoshikazu Terada, 2014. "Strong Consistency of Reduced K-means Clustering," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(4), pages 913-931, December.
25. repec:jss:jstsof:47:i05 is not listed on IDEAS
26. Alessandro Casa & Giovanna Menardi, 2022. "Nonparametric semi-supervised classification with application to signal detection in high energy physics," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(3), pages 531-550, September.