Prof. Dr. Thomas Kneib

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  • 2022 | Journal Article | 
    ​ ​Pseudo-document simulation for comparing LDA, GSDMM and GPM topic models on short and sparse text using Twitter data​
    Weisser, C.; Gerloff, C.; Thielmann, A.; Python, A.; Reuter, A.; Kneib, T.   & Säfken, B.​ (2022) 
    Computational Statistics,.​ DOI: https://doi.org/10.1007/s00180-022-01246-z 
    ​Details  DOI 
  • 2021 | Journal Article | Research Paper | 
    ​ ​Introductory data science across disciplines, using Python, case studies, and industry consulting projects​
    Lasser, J.; Manik, D.; Silbersdorff, A. ; Säfken, B. & Kneib, T. ​ (2021) 
    Teaching Statistics, 43 pp. S190​-S200​.​ DOI: https://doi.org/10.1111/test.12243 
    ​Details  DOI 
  • 2021 | Journal Article
    ​ ​Conditional Model Selection in Mixed-Effects Models with cAIC4​
    Säfken, B.; Rügamer, D.; Kneib, T.   & Greven, S.​ (2021) 
    Journal of Statistical Software, 99(8).​ DOI: https://doi.org/10.18637/jss.v099.i08 
    ​Details  DOI 
  • 2019 | Journal Article | 
    ​ ​Conditional covariance penalties for mixed models​
    Säfken, B. & Kneib, T. ​ (2019) 
    Scandinavian Journal of Statistics, 47(3) pp. 990​-1010​.​ DOI: https://doi.org/10.1111/sjos.12437 
    ​Details  DOI 
  • 2018 | Preprint
    ​ ​Conditional Model Selection in Mixed-Effects Models with cAIC4​
    Säfken, B.; Rügamer, D.; Kneib, T.  & Greven, S.​ (2018)
    ​Details  arXiv 

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Contributor:  Säfken, Benjamin

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