Prof. Dr. Thomas Kneib

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  • 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 
  • 2019 | Book Chapter
    ​ ​Mehr als Durchschnittsstatistik: ​Eine kritische Einführung in Regressionsmethoden jenseits des Mittelwertes​
    Hohberg, M. ; Silbersdorff, A.  & Kneib, T. ​ (2019)
    In: Perspektiven einer pluralen Ökonomik pp. 231​-255.  DOI: https://doi.org/10.1007/978-3-658-16145-3_10 
    ​Details  DOI 
  • 2018 | Journal Article
    ​ ​A Markov-switching generalized additive model for compound Poisson processes, with applications to operational loss models​
    Hambuckers, J.; Kneib, T. ; Langrock, R. & Silbersdorff, A. ​ (2018) 
    Quantitative Finance, 18(10) pp. 1679​-1698​.​ DOI: https://doi.org/10.1080/14697688.2017.1417625 
    ​Details  DOI 
  • 2018 | Journal Article
    ​ ​Reconsidering the income-health relationship using distributional regression​
    Silbersdorff, A. ; Lynch, J.; Klasen, S. & Kneib, T. ​ (2018) 
    Health Economics, 27(7) pp. 1074​-1088​.​ DOI: https://doi.org/10.1002/hec.3656 
    ​Details  DOI  PMID  PMC 
  • 2017 | Preprint
    ​ ​A Markov-Switching Generalized Additive Model for Compound Poisson Processes, with Applications to Operational Losses Models​
    Hambuckers, J.; Kneib, T. ; Langrock, R.& Silbersdorff, A. ​ (2017)
    ​Details 
  • 2016 | Journal Article | Research Paper
    ​ ​A Semiparametric Analysis of Conditional Income Distributions​
    Sohn, A. ; Klein, N.   & Kneib, T. ​ (2016) 
    Schmollers Jahrbuch, 135(1) pp. 13​-22​.​ DOI: https://doi.org/10.3790/schm.135.1.13 
    ​Details  DOI 
  • 2016 | Journal Article | Erratum | 
    ​ ​Correction: Bayesian structured additive distributional regression with an application to regional income inequality in Germany​
    Klein, N. ; Kneib, T. ; Lang, S. & Sohn, A. ​ (2016) 
    The Annals of Applied Statistics, 10(2) pp. 1135​-1136​.​ DOI: https://doi.org/10.1214/16-AOAS922 
    ​Details  DOI 
  • 2015 | Journal Article
    ​ ​Nonparametric inference in hidden Markov models using P-splines​
    Langrock, R. ; Kneib, T. ; Sohn, A.   & Ruiter, S. L. de​ (2015) 
    Biometrics, 71(2) pp. 520​-528​.​ DOI: https://doi.org/10.1111/biom.12282 
    ​Details  DOI 
  • 2015 | Journal Article
    ​ ​Bayesian structured additive distributional regression with an application to regional income inequality in Germany​
    Klein, N. ; Kneib, T. ; Lang, S. & Sohn, A. ​ (2015) 
    The Annals of Applied Statistics, 9(2) pp. 1024​-1052​.​ DOI: https://doi.org/10.1214/15-aoas823 
    ​Details  DOI 
  • 2014 | Journal Article
    ​ ​Semiparametric stochastic volatility modelling using penalized splines​
    Langrock, R. ; Michelot, T.; Sohn, A.   & Kneib, T. ​ (2014) 
    Computational Statistics, 30(2) pp. 517​-537​.​ DOI: https://doi.org/10.1007/s00180-014-0547-5 
    ​Details  DOI 
  • 2014 | Report
    ​ ​A New Semiparametric Approach to Analysing Conditional Income Distributions​
    Sohn, A. ; Klein, N.& Kneib, T. ​ (2014). DOI: https://doi.org/10.2139/ssrn.2404335 
    ​Details  DOI 
  • 2013 | Preprint
    ​ ​Nonparametric inference in hidden Markov models using P-splines​
    Langrock, R.; Kneib, T. ; Sohn, A.  & DeRuiter, S.​ (2013)
    ​Details  arXiv 
  • 2013 | Preprint
    ​ ​Semiparametric stochastic volatility modelling using penalized splines​
    Langrock, R.; Michelot, T.; Sohn, A.  & Kneib, T. ​ (2013)
    ​Details  arXiv 

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