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KmL: k-means for longitudinal data

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  • Christophe Genolini
  • Bruno Falissard

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  • Christophe Genolini & Bruno Falissard, 2010. "KmL: k-means for longitudinal data," Computational Statistics, Springer, vol. 25(2), pages 317-328, June.
    • Handle: RePEc:spr:compst:v:25:y:2010:i:2:p:317-328
    DOI: 10.1007/s00180-009-0178-4
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    References listed on IDEAS

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    2. Hand, David J. & Krzanowski, Wojtek J., 2005. "Optimising k-means clustering results with standard software packages," Computational Statistics & Data Analysis, Elsevier, vol. 49(4), pages 969-973, June.
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    6. Sugar, Catherine A. & James, Gareth M., 2003. "Finding the Number of Clusters in a Dataset: An Information-Theoretic Approach," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 750-763, January.
    7. Shuichi Tokushige & Hiroshi Yadohisa & Koichi Inada, 2007. "Crisp and fuzzy k-means clustering algorithms for multivariate functional data," Computational Statistics, Springer, vol. 22(1), pages 1-16, April.
    8. Luis Angel Garcia-Escudero & Alfonso Gordaliza, 2005. "A Proposal for Robust Curve Clustering," Journal of Classification, Springer;The Classification Society, vol. 22(2), pages 185-201, September.
    9. C. Abraham & P. A. Cornillon & E. Matzner‐Løber & N. Molinari, 2003. "Unsupervised Curve Clustering using B‐Splines," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 30(3), pages 581-595, September.
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    2. Manuel Marques-Cruz & Daniel Martinho Dias & João A. Fonseca & Bernardo Sousa-Pinto, 2024. "Ten year citation prediction model for systematic reviews using early years citation data," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(8), pages 4847-4862, August.
    3. I. Albarrán & P. Alonso-González & J. M. Marin, 2017. "Some criticism to a general model in Solvency II: an explanation from a clustering point of view," Empirical Economics, Springer, vol. 52(4), pages 1289-1308, June.
    4. Alonso, Pablo J., 2011. "Why using a general model in Solvency II is not a good idea : an explanation from a Bayesian point of view," DES - Working Papers. Statistics and Econometrics. WS ws113729, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Satoshi Usami & Ross Jacobucci & Timothy Hayes, 2019. "The performance of latent growth curve model-based structural equation model trees to uncover population heterogeneity in growth trajectories," Computational Statistics, Springer, vol. 34(1), pages 1-22, March.
    6. Jean-Baptiste Pingault & Sylvana M Côté & Eric Lacourse & Cédric Galéra & Frank Vitaro & Richard E Tremblay, 2013. "Childhood Hyperactivity, Physical Aggression and Criminality: A 19-Year Prospective Population-Based Study," PLOS ONE, Public Library of Science, vol. 8(5), pages 1-7, May.
    7. 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.
    8. Yu Fei & Rongli Li & Zhouhong Li & Guoqi Qian, 2024. "Clustering Longitudinal Data for Growth Curve Modelling by Gibbs Sampler and Information Criterion," Journal of Classification, Springer;The Classification Society, vol. 41(2), pages 371-401, July.
    9. Xu, Peirong & Peng, Heng & Huang, Tao, 2018. "Unsupervised learning of mixture regression models for longitudinal data," Computational Statistics & Data Analysis, Elsevier, vol. 125(C), pages 44-56.

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