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Factorial k-means analysis for two-way data

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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. Vichi, Maurizio & Saporta, Gilbert, 2009. "Clustering and disjoint principal component analysis," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3194-3208, June.
  3. Cristina Tortora & Mireille Gettler Summa & Marina Marino & Francesco Palumbo, 2016. "Factor probabilistic distance clustering (FPDC): a new clustering method," 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. 10(4), pages 441-464, December.
  4. DeSarbo, Wayne S. & Selin Atalay, A. & Blanchard, Simon J., 2009. "A three-way clusterwise multidimensional unfolding procedure for the spatial representation of context dependent preferences," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3217-3230, June.
  5. Farnè, Matteo & Vouldis, Angelos, 2017. "Business models of the banks in the euro area," Working Paper Series 2070, European Central Bank.
  6. 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.
  7. Lucadamo, Antonio & Amenta, Pietro & Leone, Natalia, 2021. "Soil texture prediction via reduced K-means Principal Component Multinomial Regression," Socio-Economic Planning Sciences, Elsevier, vol. 75(C).
  8. M. Velden & A. Iodice D’Enza & F. Palumbo, 2017. "Cluster Correspondence Analysis," Psychometrika, Springer;The Psychometric Society, vol. 82(1), pages 158-185, March.
  9. Monia Ranalli & Roberto Rocci, 2017. "A Model-Based Approach to Simultaneous Clustering and Dimensional Reduction of Ordinal Data," Psychometrika, Springer;The Psychometric Society, vol. 82(4), pages 1007-1034, December.
  10. Efthymios Costa & Ioanna Papatsouma & Angelos Markos, 2023. "Benchmarking distance-based partitioning methods for mixed-type data," 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. 17(3), pages 701-724, September.
  11. Matteo Farnè & Angelos T. Vouldis, 2021. "Banks’ business models in the euro area: a cluster analysis in high dimensions," Annals of Operations Research, Springer, vol. 305(1), pages 23-57, October.
  12. Venera Tomaselli & Mario Fordellone & Maurizio Vichi, 2021. "Building Well-Being Composite Indicator for Micro-Territorial Areas Through PLS-SEM and K-Means Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 153(2), pages 407-429, January.
  13. Van Mechelen, Iven & Schepers, Jan, 2007. "A unifying model involving a categorical and/or dimensional reduction for multimode data," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 537-549, September.
  14. Masaki Mitsuhiro & Hiroshi Yadohisa, 2015. "Reduced $$k$$ k -means clustering with MCA in a low-dimensional space," Computational Statistics, Springer, vol. 30(2), pages 463-475, June.
  15. Alfonso Iodice D’Enza & Francesco Palumbo, 2013. "Iterative factor clustering of binary data," Computational Statistics, Springer, vol. 28(2), pages 789-807, April.
  16. Roberto Rocci & Stefano Gattone & Maurizio Vichi, 2011. "A New Dimension Reduction Method: Factor Discriminant K-means," Journal of Classification, Springer;The Classification Society, vol. 28(2), pages 210-226, July.
  17. Vanessa Kuentz-Simonet & Amaury Labenne & Tina Rambonilaza, 2017. "Using ClustOfVar to Construct Quality of Life Indicators for Vulnerability Assessment Municipality Trajectories in Southwest France from 1999 to 2009," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 131(3), pages 973-997, April.
  18. Cristina Tortora & Paul D. McNicholas & Ryan P. Browne, 2016. "A mixture of generalized hyperbolic factor analyzers," 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. 10(4), pages 423-440, December.
  19. van de Velden, M. & Iodice D' Enza, A. & Palumbo, F., 2014. "Cluster Correspondence Analysis," Econometric Institute Research Papers EI 2014-24, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  20. Payne, Roger W., 2003. "General balance, large data sets and extensions to unbalanced treatment structures," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 297-304, October.
  21. Timmerman, Marieke E. & Ceulemans, Eva & Kiers, Henk A.L. & Vichi, Maurizio, 2010. "Factorial and reduced K-means reconsidered," Computational Statistics & Data Analysis, Elsevier, vol. 54(7), pages 1858-1871, July.
  22. Naoto Yamashita & Shin-ichi Mayekawa, 2015. "A new biplot procedure with joint classification of objects and variables by fuzzy c-means clustering," 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. 9(3), pages 243-266, September.
  23. 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.
  24. José Fernando Romero Cañizares & Purificación Vicente Galindo & Yannis Phillis & Evangelos Grigoroudis, 2022. "Graphical sustainability analysis using disjoint biplots," Operational Research, Springer, vol. 22(2), pages 1575-1596, April.
  25. Michio Yamamoto, 2012. "Clustering of functional data in a low-dimensional subspace," 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. 6(3), pages 219-247, October.
  26. Kensuke Tanioka & Hiroshi Yadohisa, 2019. "Simultaneous Method of Orthogonal Non-metric Non-negative Matrix Factorization and Constrained Non-hierarchical Clustering," Journal of Classification, Springer;The Classification Society, vol. 36(1), pages 73-93, April.
  27. J. Vera & Rodrigo Macías & Willem Heiser, 2013. "Cluster Differences Unfolding for Two-Way Two-Mode Preference Rating Data," Journal of Classification, Springer;The Classification Society, vol. 30(3), pages 370-396, October.
  28. 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.
  29. Uno, Kohei & Satomura, Hironori & Adachi, Kohei, 2016. "Fixed factor analysis with clustered factor score constraint," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 265-274.
  30. 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.
  31. Fordellone, Mario & Vichi, Maurizio, 2020. "Finding groups in structural equation modeling through the partial least squares algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 147(C).
  32. 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.
  33. Donatella Vicari & Paolo Giordani, 2023. "CPclus: Candecomp/Parafac Clustering Model for Three-Way Data," Journal of Classification, Springer;The Classification Society, vol. 40(2), pages 432-465, July.
  34. Michio Yamamoto & Heungsun Hwang, 2017. "Dimension-Reduced Clustering of Functional Data via Subspace Separation," Journal of Classification, Springer;The Classification Society, vol. 34(2), pages 294-326, July.
  35. Álvaro Herrero & Alfredo Jiménez & Secil Bayraktar, 2019. "Hybrid Unsupervised Exploratory Plots: A Case Study of Analysing Foreign Direct Investment," Complexity, Hindawi, vol. 2019, pages 1-14, June.
  36. Roberto Rocci & Maurizio Vichi, 2005. "Three-Mode Component Analysis with Crisp or Fuzzy Partition of Units," Psychometrika, Springer;The Psychometric Society, vol. 70(4), pages 715-736, December.
  37. Igor Kravchuk & Viktoriia Stoika, 2021. "Business Μodels of Βanks for the Financial Markets in the EU," European Research Studies Journal, European Research Studies Journal, vol. 0(2B), pages 371-382.
  38. Luca Greco & Antonio Lucadamo & Pietro Amenta, 2020. "An Impartial Trimming Approach for Joint Dimension and Sample Reduction," Journal of Classification, Springer;The Classification Society, vol. 37(3), pages 769-788, October.
  39. Jérome SARACCO & Marie CHAVENT & Vanessa KUENTZ, 2010. "Clustering of categorical variables around latent variables," Cahiers du GREThA (2007-2019) 2010-02, Groupe de Recherche en Economie Théorique et Appliquée (GREThA).
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