HDclassif: An R Package for Model-Based Clustering and Discriminant Analysis of High-Dimensional Data
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DOI: http://hdl.handle.net/10.18637/jss.v046.i06
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- Vaghefi, A. & Farzan, Farbod & Jafari, Mohsen A., 2015. "Modeling industrial loads in non-residential buildings," Applied Energy, Elsevier, vol. 158(C), pages 378-389.
- Maghrour Zefreh, Mohammad & Saif, Muhammad Atiullah & Esztergár-Kiss, Domokos & Torok, Adam, 2023. "A data-driven decision support tool for public transport service analysis and provision," Transport Policy, Elsevier, vol. 135(C), pages 82-90.
- Branislav Panić & Jernej Klemenc & Marko Nagode, 2020. "Optimizing the Estimation of a Histogram-Bin Width—Application to the Multivariate Mixture-Model Estimation," Mathematics, MDPI, vol. 8(7), pages 1-30, July.
- 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.
- Nia, Vahid Partovi & Davison, Anthony C., 2012. "High-Dimensional Bayesian Clustering with Variable Selection: The R Package bclust," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 47(i05).
- Carlo Cavicchia & Maurizio Vichi & Giorgia Zaccaria, 2022. "Gaussian mixture model with an extended ultrametric covariance structure," 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 399-427, June.
- Biecek, Przemyslaw & Szczurek, Ewa & Vingron, Martin & Tiuryn, Jerzy, 2012. "The R Package bgmm: Mixture Modeling with Uncertain Knowledge," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 47(i03).
- Kim, Nam-Hwui & Browne, Ryan P., 2021. "In the pursuit of sparseness: A new rank-preserving penalty for a finite mixture of factor analyzers," Computational Statistics & Data Analysis, Elsevier, vol. 160(C).
- Mairech, Hanene & López-Bernal, Álvaro & Moriondo, Marco & Dibari, Camilla & Regni, Luca & Proietti, Primo & Villalobos, Francisco J. & Testi, Luca, 2020. "Is new olive farming sustainable? A spatial comparison of productive and environmental performances between traditional and new olive orchards with the model OliveCan," Agricultural Systems, Elsevier, vol. 181(C).
- 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.
- Mayra Z Rodriguez & Cesar H Comin & Dalcimar Casanova & Odemir M Bruno & Diego R Amancio & Luciano da F Costa & Francisco A Rodrigues, 2019. "Clustering algorithms: A comparative approach," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-34, January.
- William Cipolli & Timothy Hanson, 2019. "Supervised learning via smoothed Polya trees," 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(4), pages 877-904, December.
- Julien Jacques & Cristian Preda, 2014. "Functional data clustering: a survey," 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. 8(3), pages 231-255, September.
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