Prof. Dr. Thomas Kneib

 
Staff Status
unigoe
 

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  • 2022 Journal Article | Research Paper | 
    ​ ​Is age at menopause decreasing? – The consequences of not completing the generational cohort​
    Martins, R.; Sousa, B. d.; Kneib, T. ; Hohberg, M. ; Klein, N. ; Duarte, E. & Rodrigues, V.​ (2022) 
    BMC Medical Research Methodology22(1) art. 187​.​ DOI: https://doi.org/10.1186/s12874-022-01658-x 
    Details  DOI 
  • 2022 Journal Article | 
    ​ ​Mapping ex ante risks of COVID‐19 in Indonesia using a Bayesian geostatistical model on airport network data​
    Seufert, J. D.; Python, A.; Weisser, C.; Cisneros, E. ; Kis-Katos, K.   & Kneib, T. ​ (2022) 
    Journal of the Royal Statistical Society: Series A (Statistics in Society), art. rssa.12866​.​ DOI: https://doi.org/10.1111/rssa.12866 
    Details  DOI 
  • 2022 Journal Article | 
    ​ ​Generalised exponential-Gaussian distribution: a method for neural reaction time analysis​
    Marmolejo-Ramos, F.; Barrera-Causil, C.; Kuang, S.; Fazlali, Z.; Wegener, D.; Kneib, T.   & De Bastiani, F. et al.​ (2022) 
    Cognitive Neurodynamics,.​ DOI: https://doi.org/10.1007/s11571-022-09813-2 
    Details  DOI 
  • 2022 Journal Article | Research Paper | 
    ​ ​Mitigating spatial confounding by explicitly correlating Gaussian random fields​
    Marques, I. ; Kneib, T.   & Klein, N.​ (2022) 
    Environmetrics33(5).​ DOI: https://doi.org/10.1002/env.2727 
    Details  DOI 
  • 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 
  • 2022 Journal Article | 
    ​ ​A non-stationary model for spatially dependent circular response data based on wrapped Gaussian processes​
    Marques, I. ; Kneib, T.   & Klein, N. ​ (2022) 
    Statistics and Computing32(5).​ DOI: https://doi.org/10.1007/s11222-022-10136-9 
    Details  DOI 
  • 2022 Journal Article | 
    ​ ​Bayesian discrete conditional transformation models​
    Carlan, M. & Kneib, T. ​ (2022) 
    Statistical Modelling, art. 1471082X2211141​.​ DOI: https://doi.org/10.1177/1471082X221114177 
    Details  DOI 
  • 2022 Journal Article | 
    ​ ​Distributional regression modeling via generalized additive models for location, scale, and shape: An overview through a data set from learning analytics​
    Marmolejo‐Ramos, F.; Tejo, M.; Brabec, M.; Kuzilek, J.; Joksimovic, S.; Kovanovic, V. & González, J. et al.​ (2022) 
    Wiley Interdisciplinary Reviews. Data Mining and Knowledge Discovery,.​ DOI: https://doi.org/10.1002/widm.1479 
    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 Statistics43 pp. S190​-S200​.​ DOI: https://doi.org/10.1111/test.12243 
    Details  DOI 
  • 2021 Journal Article | Research Paper | 
    ​ ​Environmental heterogeneity predicts global species richness patterns better than area​
    Udy, K.; Fritsch, M. ; Meyer, K. M. ; Grass, I. ; Hanß, S. ; Hartig, F. & Kneib, T.  et al.​ (2021) 
    Global Ecology and Biogeography30(4) pp. 842​-851​.​ DOI: https://doi.org/10.1111/geb.13261 
    Details  DOI 
  • 2021 Journal Article | 
    ​ ​Interactively visualizing distributional regression models with distreg.vis​
    Stadlmann, S. & Kneib, T. ​ (2021) 
    Statistical Modelling22(6) pp. 527​-545​.​ DOI: https://doi.org/10.1177/1471082X211007308 
    Details  DOI 
  • 2021 Journal Article | Research Paper | 
    ​ ​Beyond unidimensional poverty analysis using distributional copula models for mixed ordered‐continuous outcomes​
    Hohberg, M. ; Donat, F.; Marra, G. & Kneib, T. ​ (2021) 
    Journal of the Royal Statistical Society: Series C (Applied Statistics)70(5) pp. 1365​-1390​.​ DOI: https://doi.org/10.1111/rssc.12517 
    Details  DOI 
  • 2020 Journal Article | 
    ​ ​Spatio-temporal expectile regression models​
    Kneib, T. ; Otto-Sobotka, F. & Spiegel, E.​ (2020) 
    Statistical Modelling20(4) art. 1471082X1982994​.​ DOI: https://doi.org/10.1177/1471082X19829945 
    Details  DOI 
  • 2020 Journal Article | 
    ​ ​Comments on: Inference and computation with Generalized Additive Models and their extensions​
    Kneib, T. ​ (2020) 
    TEST29(2) pp. 351​-353​.​ DOI: https://doi.org/10.1007/s11749-020-00713-3 
    Details  DOI 
  • 2020 Journal Article | 
    ​ ​Generalised joint regression for count data: a penalty extension for competitive settings​
    van der Wurp, H.; Groll, A. ; Kneib, T. ; Marra, G. & Radice, R.​ (2020) 
    Statistics and Computing30(5) pp. 1419​-1432​.​ DOI: https://doi.org/10.1007/s11222-020-09953-7 
    Details  DOI 
  • 2020 Journal Article | Editorial Contribution (Editorial, Introduction, Epilogue) | 
    ​ ​Editorial​
    Kauermann, G.; Kneib, T.   & Okhrin, Y.​ (2020) 
    Advances in Statistical Analysis104(1) pp. 1​-3​.​ DOI: https://doi.org/10.1007/s10182-020-00361-w 
    Details  DOI 
  • 2020 Journal Article | 
    ​ ​Treatment effects beyond the mean using distributional regression: Methods and guidance​
    Hohberg, M. ; Pütz, P. & Kneib, T. ​ (2020) 
    PLoS One15(2) art. e0226514​.​ DOI: https://doi.org/10.1371/journal.pone.0226514 
    Details  DOI  PMID  PMC 

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