Prof. Dr. Thomas Kneib

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  • 2018 | Journal Article | Editorial Contribution (Editorial, Introduction, Epilogue)
    ​ ​Editorial 'Bridging the gap between methodology and applications: Tutorials on semiparametric regression'​
    Groll, A.; Kneib, T.   & Mayr, A.​ (2018) 
    Statistical Modelling, 18(3-4) pp. 199​-202​.​ DOI: https://doi.org/10.1177/1471082X18761252 
    ​Details  DOI 
  • 2018 | Journal Article
    ​ ​On the dependency of soccer scores – a sparse bivariate Poisson model for the UEFA European football championship 2016​
    Groll, A.; Kneib, T. ; Mayr, A. & Schauberger, G.​ (2018) 
    Journal of Quantitative Analysis in Sports, 14(2) pp. 65​-79​.​ DOI: https://doi.org/10.1515/jqas-2017-0067 
    ​Details  DOI 
  • 2017 | Preprint
    ​ ​Gradient boosting in Markov-switching generalized additive models for location, scale and shape​
    Adam, T.; Mayr, A.& Kneib, T. ​ (2017)
    ​Details  arXiv 
  • 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 
  • 2010 | Report
    ​ ​GAMLSS for high-dimensional data – a flexible approach based on boosting​
    Mayr, A.; Hofner, B.; Kneib, T.  & Schmid, M.​ (2010)
    ​Details 

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