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A Partially Linear Tree-based Regression Model for Multivariate Outcomes

Author

Listed:
  • Kai Yu
  • William Wheeler
  • Qizhai Li
  • Andrew W. Bergen
  • Neil Caporaso
  • Nilanjan Chatterjee
  • Jinbo Chen

Abstract

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Suggested Citation

  • Kai Yu & William Wheeler & Qizhai Li & Andrew W. Bergen & Neil Caporaso & Nilanjan Chatterjee & Jinbo Chen, 2010. "A Partially Linear Tree-based Regression Model for Multivariate Outcomes," Biometrics, The International Biometric Society, vol. 66(1), pages 89-96, March.
    • Handle: RePEc:bla:biomet:v:66:y:2010:i:1:p:89-96
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2009.01235.x
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    References listed on IDEAS

    as
    1. David R. Larsen & Paul L. Speckman, 2004. "Multivariate Regression Trees for Analysis of Abundance Data," Biometrics, The International Biometric Society, vol. 60(2), pages 543-549, June.
    2. Youngchao Ge & Sandrine Dudoit & Terence Speed, 2003. "Resampling-based multiple testing for microarray data analysis," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 12(1), pages 1-77, June.
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    Cited by:

    1. Hajjem, Ahlem & Bellavance, François & Larocque, Denis, 2011. "Mixed effects regression trees for clustered data," Statistics & Probability Letters, Elsevier, vol. 81(4), pages 451-459, April.
    2. Gerhard Tutz & Moritz Berger, 2018. "Tree-structured modelling of categorical predictors in generalized additive regression," 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 737-758, September.

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