Prof. Dr. Thomas Kneib

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  • 2017 | Journal Article
    ​ ​Boosting joint models for longitudinal and time-to-event data​
    Taylor-Robinson, D.; Pressler, T.; Schmid, M.; Mayr, A.; Waldmann, E. ; Klein, N.   & Kneib, T. ​ (2017) 
    Biometrical Journal, 59(6) pp. 1104-1121​-1121​.​ DOI: https://doi.org/10.1002/bimj.201600158 
    ​Details  DOI  PMID  PMC 
  • 2012 | Journal Article
    ​ ​Generalized additive models for location, scale and shape for high dimensional data-a flexible approach based on boosting​
    Mayr, A.; Fenske, N.; Hofner, B.; Kneib, T.   & Schmid, M.​ (2012) 
    Journal of the Royal Statistical Society. Series C, Applied statistics, 61(3) pp. 403​-427​.​ DOI: https://doi.org/10.1111/j.1467-9876.2011.01033.x 
    ​Details  DOI 
  • 2011 | Journal Article
    ​ ​A Framework for Unbiased Model Selection Based on Boosting​
    Hofner, B.; Hothorn, T.; Kneib, T.   & Schmid, M.​ (2011) 
    Journal of Computational and Graphical Statistics, 20(4) pp. 956​-971​.​ DOI: https://doi.org/10.1198/jcgs.2011.09220 
    ​Details  DOI 
  • 2010 | Report
    ​ ​GAMLSS for high-dimensional data – a flexible approach based on boosting​
    Mayr, A.; Hofner, B.; Kneib, T.  & Schmid, M.​ (2010)
    ​Details 
  • 2010 | Journal Article | 
    ​ ​Model-based Boosting 2.0​
    Hothorn, T.; Bühlmann, P.; Kneib, T. ; Schmid, M. & Hofner, B.​ (2010) 
    Journal of Machine Learning Reseach - Machine Learning Open Source Software, 11 pp. 2109​-2113​.​
    ​Details 

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Contributor:  Schmid, Matthias

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