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A classification EM algorithm for clustering and two stochastic versions

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Cited by:

  1. Cremaschini, Alessandro & Maruotti, Antonello, 2023. "A finite mixture analysis of structural breaks in the G-7 gross domestic product series," Research in Economics, Elsevier, vol. 77(1), pages 76-90.
  2. Zhenghao Zeng & Yuqi Gu & Gongjun Xu, 2023. "A Tensor-EM Method for Large-Scale Latent Class Analysis with Binary Responses," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 580-612, June.
  3. Songul Cinaroglu, 2020. "EU-28 Country Clusters and Patterns of Disease During the European Refugee Crisis," Journal of International Migration and Integration, Springer, vol. 21(3), pages 879-891, September.
  4. Sunghoon Kim & Ashley Stadler Blank & Wayne S. DeSarbo & Jeroen K. Vermunt, 2022. "The Spatial Representation of Consumer Dispersion Patterns via a New Multi-level Latent Class Methodology," Journal of Classification, Springer;The Classification Society, vol. 39(2), pages 218-239, July.
  5. Chenchen Ma & Jimmy Torre & Gongjun Xu, 2023. "Bridging Parametric and Nonparametric Methods in Cognitive Diagnosis," Psychometrika, Springer;The Psychometric Society, vol. 88(1), pages 51-75, March.
  6. Rasmus Lentz & Suphanit Piyapromdee & Jean-Marc Robin, 2022. "The Anatomy of Sorting - Evidence from Danish Data," SciencePo Working papers Main hal-03869383, HAL.
  7. Frei, Marco & Künsch, Hans R., 2013. "Mixture ensemble Kalman filters," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 127-138.
  8. Adelaide Figueiredo, 2017. "Clustering Directions Based on the Estimation of a Mixture of Von Mises-Fisher Distributions," The Open Statistics and Probability Journal, Bentham Open, vol. 8(1), pages 39-52, December.
  9. Adrian O’Hagan & Arthur White, 2019. "Improved model-based clustering performance using Bayesian initialization averaging," Computational Statistics, Springer, vol. 34(1), pages 201-231, March.
  10. Guan-Hua Huang & Su-Mei Wang & Chung-Chu Hsu, 2011. "Optimization-Based Model Fitting for Latent Class and Latent Profile Analyses," Psychometrika, Springer;The Psychometric Society, vol. 76(4), pages 584-611, October.
  11. François Bavaud, 2009. "Aggregation invariance in general clustering approaches," 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. 3(3), pages 205-225, December.
  12. Murphy, Thomas Brendan & Martin, Donal, 2003. "Mixtures of distance-based models for ranking data," Computational Statistics & Data Analysis, Elsevier, vol. 41(3-4), pages 645-655, January.
  13. Wicker, Nicolas & Muller, Jean & Kalathur, Ravi Kiran Reddy & Poch, Olivier, 2008. "A maximum likelihood approximation method for Dirichlet's parameter estimation," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1315-1322, January.
  14. M. Vrac & L. Billard & E. Diday & A. Chédin, 2012. "Copula analysis of mixture models," Computational Statistics, Springer, vol. 27(3), pages 427-457, September.
  15. Christophe Ambroise & Gérard Govaert, 1996. "Constrained clustering and Kohonen Self-Organizing Maps," Journal of Classification, Springer;The Classification Society, vol. 13(2), pages 299-313, September.
  16. Volkovich, Vladimir & Kogan, Jacob & Nicholas, Charles, 2007. "Building initial partitions through sampling techniques," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1097-1105, December.
  17. Volodymyr Melnykov & Semhar Michael, 2020. "Clustering Large Datasets by Merging K-Means Solutions," Journal of Classification, Springer;The Classification Society, vol. 37(1), pages 97-123, April.
  18. Yannis Marinakis & Magdalene Marinaki & Michael Doumpos & Nikolaos Matsatsinis & Constantin Zopounidis, 2011. "A hybrid ACO-GRASP algorithm for clustering analysis," Annals of Operations Research, Springer, vol. 188(1), pages 343-358, August.
  19. Fritz, Heinrich & García-Escudero, Luis A. & Mayo-Iscar, Agustín, 2012. "tclust: An R Package for a Trimming Approach to Cluster Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 47(i12).
  20. Rasmus Lentz & Suphanit Piyapromdee & Jean-Marc Robin, 2018. "On Worker and Firm Heterogeneity in Wages and Employment Mobility: Evidence from Danish Register Data," PIER Discussion Papers 91, Puey Ungphakorn Institute for Economic Research.
  21. Biernacki, Christophe & Celeux, Gilles & Govaert, Gerard, 2003. "Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 41(3-4), pages 561-575, January.
  22. Sharon M. McNicholas & Paul D. McNicholas & Daniel A. Ashlock, 2021. "An Evolutionary Algorithm with Crossover and Mutation for Model-Based Clustering," Journal of Classification, Springer;The Classification Society, vol. 38(2), pages 264-279, July.
  23. García-Escudero, L.A. & Gordaliza, A. & Mayo-Iscar, A. & San Martín, R., 2010. "Robust clusterwise linear regression through trimming," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3057-3069, December.
  24. Keiji Takai, 2012. "Constrained EM algorithm with projection method," Computational Statistics, Springer, vol. 27(4), pages 701-714, December.
  25. Zaheer Ahmed & Alberto Cassese & Gerard Breukelen & Jan Schepers, 2023. "E-ReMI: Extended Maximal Interaction Two-mode Clustering," Journal of Classification, Springer;The Classification Society, vol. 40(2), pages 298-331, July.
  26. Bouveyron, C. & Girard, S. & Schmid, C., 2007. "High-dimensional data clustering," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 502-519, September.
  27. Volodymyr Melnykov & Xuwen Zhu, 2019. "An extension of the K-means algorithm to clustering skewed data," Computational Statistics, Springer, vol. 34(1), pages 373-394, March.
  28. Kostov, Philip & McErlean, Seamus, 2006. "Using the mixtures-of-distributions technique for the classification of farms into representative farms," Agricultural Systems, Elsevier, vol. 88(2-3), pages 528-537, June.
  29. repec:jss:jstsof:28:i04 is not listed on IDEAS
  30. Lin, Tsung-I, 2014. "Learning from incomplete data via parameterized t mixture models through eigenvalue decomposition," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 183-195.
  31. Same, Allou & Ambroise, Christophe & Govaert, Gerard, 2006. "A classification EM algorithm for binned data," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 466-480, November.
  32. Johannes Blömer & Sascha Brauer & Kathrin Bujna & Daniel Kuntze, 2020. "How well do SEM algorithms imitate EM algorithms? A non-asymptotic analysis for mixture models," 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. 14(1), pages 147-173, March.
  33. Grün, Bettina & Leisch, Friedrich, 2008. "FlexMix Version 2: Finite Mixtures with Concomitant Variables and Varying and Constant Parameters," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 28(i04).
  34. Govaert, Gérard & Nadif, Mohamed, 2008. "Block clustering with Bernoulli mixture models: Comparison of different approaches," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3233-3245, February.
  35. Genolini, Christophe & Alacoque, Xavier & Sentenac, Mariane & Arnaud, Catherine, 2015. "kml and kml3d: R Packages to Cluster Longitudinal Data," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 65(i04).
  36. Hwang, Jung Yoon & Kuo, Way, 2007. "Model-based clustering for integrated circuit yield enhancement," European Journal of Operational Research, Elsevier, vol. 178(1), pages 143-153, April.
  37. Heath, Jeffrey W. & Fu, Michael C. & Jank, Wolfgang, 2009. "New global optimization algorithms for model-based clustering," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 3999-4017, October.
  38. Govaert, Gerard & Nadif, Mohamed, 2007. "Clustering of contingency table and mixture model," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1055-1066, December.
  39. James G. Booth & George Casella & James P. Hobert, 2008. "Clustering using objective functions and stochastic search," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(1), pages 119-139, February.
  40. Faicel Chamroukhi, 2016. "Piecewise Regression Mixture for Simultaneous Functional Data Clustering and Optimal Segmentation," Journal of Classification, Springer;The Classification Society, vol. 33(3), pages 374-411, October.
  41. Yves Grandvalet & Yoshua Bengio, 2004. "Learning from Partial Labels with Minimum Entropy," CIRANO Working Papers 2004s-28, CIRANO.
  42. Rocci, Roberto & Vichi, Maurizio, 2008. "Two-mode multi-partitioning," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 1984-2003, January.
  43. Anahita Nodehi & Mousa Golalizadeh & Mehdi Maadooliat & Claudio Agostinelli, 2021. "Estimation of parameters in multivariate wrapped models for data on a p-torus," Computational Statistics, Springer, vol. 36(1), pages 193-215, March.
  44. Roberto Mari & Salvatore Ingrassia & Antonio Punzo, 2023. "Local and Overall Deviance R-Squared Measures for Mixtures of Generalized Linear Models," Journal of Classification, Springer;The Classification Society, vol. 40(2), pages 233-266, July.
  45. Rasmus Lentz & Suphanit Piyapromdee & Jean‐Marc Robin, 2023. "The Anatomy of Sorting—Evidence From Danish Data," Econometrica, Econometric Society, vol. 91(6), pages 2409-2455, November.
  46. Fujita, André & Takahashi, Daniel Y. & Patriota, Alexandre G., 2014. "A non-parametric method to estimate the number of clusters," Computational Statistics & Data Analysis, Elsevier, vol. 73(C), pages 27-39.
  47. Jüri Lember & Joonas Sova, 2021. "Regenerativity of Viterbi Process for Pairwise Markov Models," Journal of Theoretical Probability, Springer, vol. 34(1), pages 1-33, March.
  48. Hornik, Kurt & Grün, Bettina, 2014. "movMF: An R Package for Fitting Mixtures of von Mises-Fisher Distributions," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 58(i10).
  49. Melnykov, Yana & Melnykov, Volodymyr & Zhu, Xuwen, 2017. "Studying contributions of variables to classification," Statistics & Probability Letters, Elsevier, vol. 129(C), pages 318-325.
  50. Chehade, Abdallah & Savargaonkar, Mayuresh & Krivtsov, Vasiliy, 2022. "Conditional Gaussian mixture model for warranty claims forecasting," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
  51. Hofmeyr, David P., 2020. "Degrees of freedom and model selection for k-means clustering," Computational Statistics & Data Analysis, Elsevier, vol. 149(C).
  52. Marino, Maria Francesca & Pandolfi, Silvia, 2022. "Hybrid maximum likelihood inference for stochastic block models," Computational Statistics & Data Analysis, Elsevier, vol. 171(C).
  53. Aghiles Salah & Mohamed Nadif, 2019. "Directional co-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. 13(3), pages 591-620, September.
  54. 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.
  55. Gérard Govaert & Mohamed Nadif, 2018. "Mutual information, phi-squared and model-based co-clustering for contingency tables," 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. 12(3), pages 455-488, September.
  56. Zhaotong Lin & Yangqing Deng & Wei Pan, 2021. "Combining the strengths of inverse-variance weighting and Egger regression in Mendelian randomization using a mixture of regressions model," PLOS Genetics, Public Library of Science, vol. 17(11), pages 1-25, November.
  57. Anastasios Bellas & Charles Bouveyron & Marie Cottrell & Jérôme Lacaille, 2013. "Model-based clustering of high-dimensional data streams with online mixture of probabilistic PCA," 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. 7(3), pages 281-300, September.
  58. Govaert, G. & Nadif, M., 1996. "Comparison of the mixture and the classification maximum likelihood in cluster analysis with binary data," Computational Statistics & Data Analysis, Elsevier, vol. 23(1), pages 65-81, November.
  59. L. A. García‐Escudero & A. Gordaliza & R. San Martín & S. Van Aelst & R. Zamar, 2009. "Robust linear clustering," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(1), pages 301-318, January.
  60. Xing, Xin & Xie, Rui & Zhong, Wenxuan, 2022. "Model-based sparse coding beyond Gaussian independent model," Computational Statistics & Data Analysis, Elsevier, vol. 166(C).
  61. Xuwen Zhu, 2019. "Probability of misclassification in model-based clustering," Computational Statistics, Springer, vol. 34(3), pages 1427-1442, September.
  62. Nicolas Jouvin & Pierre Latouche & Charles Bouveyron & Guillaume Bataillon & Alain Livartowski, 2021. "Greedy clustering of count data through a mixture of multinomial PCA," Computational Statistics, Springer, vol. 36(1), pages 1-33, March.
  63. Mi, Lingyun & Xu, Ting & Sun, Yuhuan & Yang, Hang & Wang, Bangjun & Gan, Xiaoli & Qiao, Lijie, 2021. "Promoting differentiated energy savings: Analysis of the psychological motivation of households with different energy consumption levels," Energy, Elsevier, vol. 218(C).
  64. Francesco Dotto & Alessio Farcomeni & Luis Angel García-Escudero & Agustín Mayo-Iscar, 2017. "A fuzzy approach to robust regression 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. 11(4), pages 691-710, December.
  65. Yurong Xie & Di Wu & Zhe Qiang, 2023. "An Improved Mixture Model of Gaussian Processes and Its Classification Expectation–Maximization Algorithm," Mathematics, MDPI, vol. 11(10), pages 1-19, May.
  66. Shuchismita Sarkar & Volodymyr Melnykov & Rong Zheng, 2020. "Gaussian mixture modeling and model-based clustering under measurement inconsistency," 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. 14(2), pages 379-413, June.
  67. Hu, Tianming & Sung, Sam Yuan, 2006. "A hybrid EM approach to spatial clustering," Computational Statistics & Data Analysis, Elsevier, vol. 50(5), pages 1188-1205, March.
  68. Christophe Genolini & Bruno Falissard, 2010. "KmL: k-means for longitudinal data," Computational Statistics, Springer, vol. 25(2), pages 317-328, June.
  69. Hien Nguyen & Geoffrey McLachlan, 2015. "Maximum likelihood estimation of Gaussian mixture models without matrix operations," 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(4), pages 371-394, December.
  70. Keefe Murphy & T. Brendan Murphy & Raffaella Piccarreta & I. Claire Gormley, 2021. "Clustering longitudinal life‐course sequences using mixtures of exponential‐distance models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(4), pages 1414-1451, October.
  71. Kindberg-Hanlon,Gene & Okou,Cedric Iltis Finafa, 2020. "Productivity Convergence : Is Anyone Catching Up?," Policy Research Working Paper Series 9378, The World Bank.
  72. Luis García-Escudero & Alfonso Gordaliza & Carlos Matrán & Agustín Mayo-Iscar, 2010. "A review of robust clustering methods," 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. 4(2), pages 89-109, September.
  73. Biernacki, Christophe & Celeux, Gilles & Govaert, Gerard & Langrognet, Florent, 2006. "Model-based cluster and discriminant analysis with the MIXMOD software," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 587-600, November.
  74. Mukhopadhyay, Subhadeep & Ghosh, Anil K., 2011. "Bayesian multiscale smoothing in supervised and semi-supervised kernel discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2344-2353, July.
  75. Fritz, Heinrich & García-Escudero, Luis A. & Mayo-Iscar, Agustín, 2013. "A fast algorithm for robust constrained clustering," Computational Statistics & Data Analysis, Elsevier, vol. 61(C), pages 124-136.
  76. Kuster, Christian & Álvarez, Jorge & Lezcano, Mikaela & Álvarez-Vaz, Ramón Dr., 2022. "Desempeño Económico De Las Empresas Agropecuarias Uruguayas: Estudio Sobre Su Evolución A Través De La Técnica De Clústers Longitudinales A Partir De Datos Contables (Economic Performance Of Uruguayan," OSF Preprints p8zk9, Center for Open Science.
  77. Luísa Novais & Susana Faria, 2021. "Comparison of the EM, CEM and SEM algorithms in the estimation of finite mixtures of linear mixed models: a simulation study," Computational Statistics, Springer, vol. 36(4), pages 2507-2533, December.
  78. Luca Bagnato & Antonio Punzo, 2013. "Finite mixtures of unimodal beta and gamma densities and the $$k$$ -bumps algorithm," Computational Statistics, Springer, vol. 28(4), pages 1571-1597, August.
  79. Langevin, R.;, 2024. "Consistent Estimation of Finite Mixtures: An Application to Latent Group Panel Structures," Health, Econometrics and Data Group (HEDG) Working Papers 24/16, HEDG, c/o Department of Economics, University of York.
  80. Xavier Bry & Lionel Cucala, 2022. "A von Mises–Fisher mixture model for clustering numerical and categorical variables," 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. 16(2), pages 429-455, June.
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