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Generalized regression trees

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  • Ciampi, Antonio

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  • Ciampi, Antonio, 1991. "Generalized regression trees," Computational Statistics & Data Analysis, Elsevier, vol. 12(1), pages 57-78, August.
    • Handle: RePEc:eee:csdana:v:12:y:1991:i:1:p:57-78
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    Citations

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    Cited by:

    1. Alessandra De Rose & Alessandro Pallara, 1997. "Survival Trees: An Alternative Non-Parametric Multivariate Technique for Life History Analysis," European Journal of Population, Springer;European Association for Population Studies, vol. 13(3), pages 223-241, September.
    2. Elise Dusseldorp & Jacqueline Meulman, 2004. "The regression trunk approach to discover treatment covariate interaction," Psychometrika, Springer;The Psychometric Society, vol. 69(3), pages 355-374, September.
    3. Tomàs Aluja-Banet & Eduard Nafria, 2003. "Stability and scalability in decision trees," Computational Statistics, Springer, vol. 18(3), pages 505-520, September.
    4. Joel Corrêa da Rosa & Álvaro Veiga & Marcelo C. Medeiros, 2003. "Three-structured smooth transition regression models based on CART algorithm," Textos para discussão 469, Department of Economics PUC-Rio (Brazil).
    5. Ahn, Hongshik, 1996. "Log-normal regression modeling through recursive partitioning," Computational Statistics & Data Analysis, Elsevier, vol. 21(4), pages 381-398, April.
    6. Kagie, M. & van Wezel, M.C. & Groenen, P.J.F., 2008. "Choosing Attribute Weights for Item Dissimilarity using Clikstream Data with an Application to a Product Catalog Map," ERIM Report Series Research in Management ERS-2008-024-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    7. Christophe Dutang & Quentin Guibert, 2021. "An explicit split point procedure in model-based trees allowing for a quick fitting of GLM trees and GLM forests," Post-Print hal-03448250, HAL.
    8. Nan-Ting Liu & Feng-Chang Lin & Yu-Shan Shih, 2020. "Count regression 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. 14(1), pages 5-27, March.
    9. Hecker, Hartmut & Wubbelt, Peter, 1997. "Clustering by response: CBR," Computational Statistics & Data Analysis, Elsevier, vol. 24(2), pages 193-215, April.
    10. L. Lombardo & M. Cama & C. Conoscenti & M. Märker & E. Rotigliano, 2015. "Binary logistic regression versus stochastic gradient boosted decision trees in assessing landslide susceptibility for multiple-occurring landslide events: application to the 2009 storm event in Messi," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 79(3), pages 1621-1648, December.
    11. Bárcena Ruiz, María Jesús & Tusell Palmer, Fernando Jorge, 2002. "Multivariate Data Imputation using Trees," BILTOKI 1134-8984, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
    12. Wei-Yin Loh, 2014. "Fifty Years of Classification and Regression Trees," International Statistical Review, International Statistical Institute, vol. 82(3), pages 329-348, December.
    13. da Rosa, Joel Correa & Veiga, Alvaro & Medeiros, Marcelo C., 2008. "Tree-structured smooth transition regression models," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2469-2488, January.

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