Prof. Dr. Thomas Kneib

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  • 2019 | Preprint
    ​ ​Noncrossing structured additive multiple-output Bayesian quantile regression models​
    Santos, B.& Kneib, T. ​ (2019)
    ​Details 
  • 2019 | Preprint
    ​ ​Generalised Joint Regression for Count Data with a Focus on Modelling Football Matches​
    van der Wurp, H.; Groll, A. H. ; Kneib, T.  & Marra, G.​ (2019)
    ​Details 
  • 2019 | Preprint
    ​ ​Operational risk, uncertainty, and the economy: a smooth transition extreme value approach​
    Hambuckers, J.& Kneib, T. ​ (2019)
    ​Details 
  • 2019 | Journal Article
    ​ ​Candidate-gene association analysis for a continuous phenotype with a spike at zero using parent-offspring trios​
    Klein, N. ; Entwistle, A.; Rosenberger, A. ; Kneib, T.   & Bickeböller, H. ​ (2019) 
    Journal of Applied Statistics, pp. 1​-15​.​ DOI: https://doi.org/10.1080/02664763.2019.1704226 
    ​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 
  • 2019 | Journal Article
    ​ ​LASSO-type penalization in the framework of generalized additive models for location, scale and shape​
    Groll, A.; Hambuckers, J.; Kneib, T.   & Umlauf, N.​ (2019) 
    Computational Statistics & Data Analysis, 140 pp. 59​-73​.​ DOI: https://doi.org/10.1016/j.csda.2019.06.005 
    ​Details  DOI 
  • 2019 | Journal Article
    ​ ​Multivariate effect priors in bivariate semiparametric recursive Gaussian models​
    Thaden, H.; Klein, N. & Kneib, T. ​ (2019) 
    Computational Statistics & Data Analysis, 137 pp. 51​-66​.​ DOI: https://doi.org/10.1016/j.csda.2018.12.004 
    ​Details  DOI 
  • 2019 | Journal Article
    ​ ​Modular regression - a Lego system for building structured additive distributional regression models with tensor product interactions​
    Kneib, T. ; Klein, N.; Lang, S. & Umlauf, N.​ (2019) 
    Test: an official journal of the Spanish Society of Statistics and Operations Research, 28(1) pp. 1​-39​.​ DOI: https://doi.org/10.1007/s11749-019-00631-z 
    ​Details  DOI 
  • 2019 | Journal Article
    ​ ​Rejoinder on: Modular regression - a Lego system for building structured additive distributional regression models with tensor product interactions​
    Kneib, T. ; Klein, N.; Lang, S. & Umlauf, N.​ (2019) 
    Test: an official journal of the Spanish Society of Statistics and Operations Research, 28(1) pp. 55​-59​.​ DOI: https://doi.org/10.1007/s11749-019-00636-8 
    ​Details  DOI 
  • 2019 | Journal Article | Erratum
    ​ ​Correction to: On the behaviour of marginal and conditional AIC in linear mixed models​
    Greven, S. & Kneib, T. ​ (2019) 
    Biometrika, art. asz051​.​ DOI: https://doi.org/10.1093/biomet/asz051 
    ​Details  DOI 
  • 2019 | Preprint
    ​ ​Using the Softplus Function to Construct Alternative Link Functions in Generalized Linear Models and Beyond​
    Wiemann, P.& Kneib, T. ​ (2019)
    ​Details 
  • 2019 | Preprint
    ​ ​Beyond unidimensional poverty analysis using distributional copula models for mixed ordered-continuous outcomes​
    Hohberg, M. ; Donat, F.; Marra, G.& Kneib, T. ​ (2019)
    ​Details 
  • 2019 | Journal Article
    ​ ​A trivariate additive regression model with arbitrary link functions and varying correlation matrix​
    Filippou, P.; Kneib, T. ; Marra, G. & Radice, R.​ (2019) 
    Journal of Statistical Planning and Inference, 199 pp. 236​-248​.​ DOI: https://doi.org/10.1016/j.jspi.2018.07.002 
    ​Details  DOI 
  • 2019 | Preprint
    ​ ​A multi-locus genetic risk score modulates social buffering of HPA axis activity in wild male primates​
    Gutleb, D. R.; Roos, C.; Heistermann, M.; De Moor, D.; Kneib, T. ; Noll, A.& Schülke, O. et al.​ (2019)
    ​Details 
  • 2019 | Journal Article
    ​ ​Directional bivariate quantiles: a robust approach based on the cumulative distribution function​
    Klein, N. & Kneib, T. ​ (2019) 
    Advances in Statistical Analysis,.​ DOI: https://doi.org/10.1007/s10182-019-00355-3 
    ​Details  DOI 
  • 2019 | Preprint
    ​ ​distreg.vis: Interactively visualizing distributional regression models​
    Stadlmann, S.& Kneib, T. ​ (2019)
    ​Details 
  • 2019 | Journal Article
    ​ ​Bayesian measurement error correction in structured additive distributional regression with an application to the analysis of sensor data on soil–plant variability​
    Pollice, A.; Jona Lasinio, G.; Rossi, R.; Amato, M.; Kneib, T.   & Lang, S.​ (2019) 
    Stochastic Environmental Research and Risk Assessment, 33(3) pp. 747​-763​.​ DOI: https://doi.org/10.1007/s00477-019-01667-1 
    ​Details  DOI 
  • 2019 | Journal Article
    ​ ​Adaptive semiparametric M-quantile regression​
    Otto-Sobotka, F.; Salvati, N.; Ranalli, M. G. & Kneib, T. ​ (2019) 
    Econometrics and Statistics, 11 pp. 116​-129​.​ DOI: https://doi.org/10.1016/j.ecosta.2019.03.001 
    ​Details  DOI 
  • 2019 | Journal Article | 
    ​ ​Rocks rock: the importance of rock formations as resting sites of the Eurasian lynx Lynx lynx​
    Signer, J. ; Filla, M.; Schoneberg, S.; Kneib, T. ; Bufka, L.; Belotti, E. & Heurich, M.​ (2019) 
    Wildlife Biology, 2019(1).​ DOI: https://doi.org/10.2981/wlb.00489 
    ​Details  DOI 
  • 2019 | Journal Article | Research Paper | 
    ​ ​Reducing Fertilizer and Avoiding Herbicides in Oil Palm Plantations - Ecological and Economic Valuations​
    Darras, K. F. A. ; Corre, M. D. ; Formaglio, G.; Tjoa, A.; Potapov, A. ; Brambach, F.   & Sibhatu, K. T.  et al.​ (2019) 
    Frontiers in Forests and Global Change, 2.​ DOI: https://doi.org/10.3389/ffgc.2019.00065 
    ​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 
  • 2019 | Journal Article
    ​ ​Assessing the relationship between markers of glycemic control through flexible copula regression models​
    Espasandín-Domínguez, J.; Cadarso-Suárez, C.; Kneib, T. ; Marra, G.; Klein, N.; Radice, R. & Lado-Baleato, O. et al.​ (2019) 
    Statistics in Medicine, 38(27) pp. 5161​-5181​.​ DOI: https://doi.org/10.1002/sim.8358 
    ​Details  DOI  PMID  PMC 
  • 2019 | Journal Article
    ​ ​Lost in Translation: On the Problem of Data Coding in Penalized Whole Genome Regression with Interactions​
    Martini, J. W R; Rosales, F.; Ha, N.-T.; Heise, J.; Wimmer, V. & Kneib, T. ​ (2019) 
    G3: Genes, Genomes, Genetics, 9(4) pp. 1117​-1129​.​ DOI: https://doi.org/10.1534/g3.118.200961 
    ​Details  DOI  PMID  PMC 
  • 2019 | Journal Article
    ​ ​Mixed binary-continuous copula regression models with application to adverse birth outcomes​
    Klein, N. ; Kneib, T. ; Marra, G.; Radice, R.; Rokicki, S. & McGovern, M. E.​ (2019) 
    Statistics in Medicine, 38(3) pp. 413​-436​.​ DOI: https://doi.org/10.1002/sim.7985 
    ​Details  DOI  PMID  PMC 
  • 2018 | Preprint
    ​ ​Generalized additive models for location, scale and shape for program evaluation: ​A guide to practice​
    Hohberg, M. ; Pütz, P.  & Kneib, T. ​ (2018)
    ​Details 
  • 2018 | Preprint
    ​ ​Conditional Model Selection in Mixed-Effects Models with cAIC4​
    Säfken, B.; Rügamer, D.; Kneib, T.  & Greven, S.​ (2018)
    ​Details  arXiv 
  • 2018 | Preprint
    ​ ​Understanding the Economic Determinants of the Severity of Operational Losses: A Regularized Generalized Pareto Regression Approach​
    Hambuckers, J.; Groll, A.& Kneib, T. ​ (2018)
    ​Details 
  • 2018 | Journal Article
    ​ ​A primer on Bayesian distributional regression​
    Umlauf, N. & Kneib, T. ​ (2018) 
    Statistical Modelling, 18(3-4) pp. 219​-247​.​ DOI: https://doi.org/10.1177/1471082X18759140 
    ​Details  DOI 
  • 2018 | Journal Article
    ​ ​Understanding the economic determinants of the severity of operational losses: A regularized generalized Pareto regression approach​
    Hambuckers, J.; Groll, A. & Kneib, T. ​ (2018) 
    Journal of Applied Econometrics, 33(6) pp. 898​-935​.​ DOI: https://doi.org/10.1002/jae.2638 
    ​Details  DOI 
  • 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 | Editorial Contribution (Editorial, Introduction, Epilogue)
    ​ ​Editorial: Special issue on quantile regression and semiparametric methods​
    He, X.; Kneib, T. ; Lamarche, C. & Wang, L.​ (2018) 
    Econometrics and Statistics, 8 pp. 1​-2​.​ DOI: https://doi.org/10.1016/j.ecosta.2018.09.002 
    ​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 
  • 2018 | Preprint
    ​ ​A Behavioral Economic Perspective on Demand Responsive Transportation​
    Herbst, H.; Minnich, A.; Herminghaus, S.; Kneib, T. ; Wacker, B.& Schlüter, J. C.​ (2018)
    ​Details 
  • 2018 | Journal Article
    ​ ​Studying the occurrence and burnt area of wildfires using zero-one-inflated structured additive beta regression​
    Ríos-Pena, L.; Kneib, T. ; Cadarso-Suárez, C.; Klein, N. & Marey-Pérez, M.​ (2018) 
    Environmental Modelling & Software, 110 pp. 107​-118​.​ DOI: https://doi.org/10.1016/j.envsoft.2018.03.008 
    ​Details  DOI 
  • 2018 | Journal Article
    ​ ​Bayesian Multivariate Distributional Regression With Skewed Responses and Skewed Random Effects​
    Michaelis, P.; Klein, N. & Kneib, T. ​ (2018) 
    Journal of Computational and Graphical Statistics, 27(3) pp. 602​-611​.​ DOI: https://doi.org/10.1080/10618600.2017.1395343 
    ​Details  DOI 
  • 2018 | Journal Article
    ​ ​Flexible estimation of time-varying effects for frequently purchased retail goods: a modeling approach based on household panel data​
    Baumgartner, B.; Guhl, D.; Kneib, T.   & Steiner, W. J.​ (2018) 
    OR Spectrum, 40(4) pp. 837​-873​.​ DOI: https://doi.org/10.1007/s00291-018-0530-6 
    ​Details  DOI 
  • 2018 | Journal Article
    ​ ​Structural Equation Models for Dealing With Spatial Confounding​
    Thaden, H. & Kneib, T. ​ (2018) 
    The American Statistician, 72(3) pp. 239​-252​.​ DOI: https://doi.org/10.1080/00031305.2017.1305290 
    ​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
    ​ ​Estimating time-varying parameters in brand choice models: A semiparametric approach​
    Guhl, D.; Baumgartner, B.; Kneib, T.   & Steiner, W. J.​ (2018) 
    International Journal of Research in Marketing, 35(3) pp. 394​-414​.​ DOI: https://doi.org/10.1016/j.ijresmar.2018.03.003 
    ​Details  DOI 
  • 2018 | Journal Article
    ​ ​Geographical differences in blood potassium detected using a structured additive distributional regression model​
    Espasandín-Domínguez, J.; Benítez-Estévez, A. J.; Cadarso-Suárez, C.; Kneib, T. ; Barreiro-Martínez, T.; Casas-Méndez, B. & Gude, F.​ (2018) 
    Spatial Statistics, 24 pp. 1​-13​.​ DOI: https://doi.org/10.1016/j.spasta.2018.03.001 
    ​Details  DOI 
  • 2018 | Journal Article | 
    ​ ​Vulnerability to poverty revisited: Flexible modeling and better predictive performance​
    Hohberg, M. ; Landau, K.; Kneib, T. ; Klasen, S.   & Zucchini, W. ​ (2018) 
    The Journal of Economic Inequality, pp. 1​-16​.​ DOI: https://doi.org/10.1007/s10888-017-9374-6 
    ​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 
  • 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 | Preprint
    ​ ​Determinants of the Variability of Oxygen Saturation during the First Minutes of Life of Term Neonates​
    Mascarenhas, A.; Marques, F.; Silva, S.; Gouveia, S.; Alves, M.; Virella, D.& Papoila, A. L. et al.​ (2017)
    ​Details 
  • 2017 | Journal Article
    ​ ​Generalized additive models with flexible response functions​
    Spiegel, E.; Kneib, T.   & Otto-Sobotka, F.​ (2017) 
    Statistics and Computing, 29(1) pp. 123​-138​.​ DOI: https://doi.org/10.1007/s11222-017-9799-6 
    ​Details  DOI 
  • 2017 | Journal Article
    ​ ​A penalized spline estimator for fixed effects panel data models​
    Pütz, P. & Kneib, T. ​ (2017) 
    Advances in Statistical Analysis, 102(2) pp. 145​-166​.​ DOI: https://doi.org/10.1007/s10182-017-0296-1 
    ​Details  DOI 
  • 2017 | Journal Article | 
    ​ ​Model selection in semiparametric expectile regression​
    Spiegel, E. ; Sobotka, F. & Kneib, T. ​ (2017) 
    Electronic Journal of Statistics, 11(2) pp. 3008​-3038​.​ DOI: https://doi.org/10.1214/17-EJS1307 
    ​Details  DOI 
  • 2017 | Journal Article | 
    ​ ​The effect of income on democracy revisited a flexible distributional approach​
    Idzalika, R.; Kneib, T.   & Martinez-Zarzoso, I.​ (2017) 
    Empirical Economics, 56(4) pp. 1207​-1230​.​ DOI: https://doi.org/10.1007/s00181-017-1390-7 
    ​Details  DOI 
  • 2017 | Journal Article | 
    ​ ​Markov-switching generalized additive models​
    Langrock, R. ; Kneib, T. ; Glennie, R. & Michelot, T.​ (2017) 
    Statistics and Computing, 27(1) pp. 259​-270​.​ DOI: https://doi.org/10.1007/s11222-015-9620-3 
    ​Details  DOI 
  • 2017 | Journal Article
    ​ ​Predicting the occurrence of wildfires with binary structured additive regression models​
    Ríos-Pena, L.; Kneib, T. ; Cadarso-Suárez, C. & Marey-Pérez, M.​ (2017) 
    Journal of Environmental Management, 187 pp. 154​-165​.​ DOI: https://doi.org/10.1016/j.jenvman.2016.11.044 
    ​Details  DOI  PMID  PMC 
  • 2017 | Journal Article | Editorial Contribution (Editorial, Introduction, Epilogue)
    ​ ​Editorial "Joint modeling of longitudinal and time-to-event data and beyond"​
    Cadarso Suárez, C.; Klein, N.; Kneib, T. ; Molenberghs, G. & Rizopoulos, D.​ (2017) 
    Biometrical Journal, 59(6) pp. 1101​-1103​.​ DOI: https://doi.org/10.1002/bimj.201700180 
    ​Details  DOI  PMID  PMC 
  • 2017 | Journal Article
    ​ ​Structured additive distributional regression for analysing landings per unit effort in fisheries research​
    Mamouridis, V.; Klein, N. ; Kneib, T. ; Cadarso Suarez, C. & Maynou, F.​ (2017) 
    Mathematical Biosciences, 283 pp. 145​-154​.​ DOI: https://doi.org/10.1016/j.mbs.2016.11.016 
    ​Details  DOI  PMID  PMC 
  • 2017 | Journal Article | 
    ​ ​Updated Nomogram Incorporating Percentage of Positive Cores to Predict Probability of Lymph Node Invasion in Prostate Cancer Patients Undergoing Sentinel Lymph Node Dissection​
    Winter, A.; Kneib, T. ; Wasylow, C.; Reinhardt, L.; Henke, R.-P.; Engels, S. & Gerullis, H. et al.​ (2017) 
    Journal of Cancer, 8(14) pp. 2692​-2698​.​ DOI: https://doi.org/10.7150/jca.20409 
    ​Details  DOI  PMID  PMC 
  • 2016 | Journal Article
    ​ ​Analysing farmland rental rates using Bayesian geoadditive quantile regression​
    März, A.; Klein, N. ; Kneib, T.   & Mußhoff, O. ​ (2016) 
    European Review of Agricultural Economics, 43(4) pp. 663​-698​.​ DOI: https://doi.org/10.1093/erae/jbv028 
    ​Details  DOI 
  • 2016 | Journal Article
    ​ ​Smoothing Parameter and Model Selection for General Smooth Models Comment​
    Kneib, T. ​ (2016) 
    Journal of the American Statistical Association, 111(516) pp. 1563​-1565​.​ DOI: https://doi.org/10.1080/01621459.2016.1250576 
    ​Details  DOI  WoS 
  • 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 
  • 2016 | Journal Article | 
    ​ ​Impact of chronic hepatitis C on mortality in cirrhotic patients admitted to intensive-care unit​
    Álvaro-Meca, A.; Jiménez-Sousa, M. A.; Boyer, A.; Medrano, J.; Reulen, H.; Kneib, T.   & Resino, S.​ (2016) 
    BMC Infectious Diseases, 16(1) art. 122​.​ DOI: https://doi.org/10.1186/s12879-016-1448-8 
    ​Details  DOI 
  • 2016 | Journal Article | 
    ​ ​Epidemiological and Ecological Characterization of the EHEC O104:H4 Outbreak in Hamburg, Germany, 2011​
    Tahden, M.; Manitz, J. ; Baumgardt, K.; Fell, G.; Kneib, T.   & Hegasy, G.​ (2016) 
    PLOS ONE, 11(10) art. e0164508​.​ DOI: https://doi.org/10.1371/journal.pone.0164508 
    ​Details  DOI  PMID  PMC 
  • 2016 | Journal Article
    ​ ​Structured fusion lasso penalized multi-state models​
    Sennhenn-Reulen, H.   & Kneib, T. ​ (2016) 
    Statistics in Medicine, 35(25) pp. 4637​-4659​.​ DOI: https://doi.org/10.1002/sim.7017 
    ​Details  DOI  PMID  PMC 
  • 2015 | Review
    ​ ​Applied Statistical Inference: Likelihood and Bayes. L.Held and D.Sabanés Bové (2014). Heidelberg: Springer. 376 pages, ISBN: 3642378862​
    Kneib, T. ​ (2015)
    Biometrical Journal, 57​(2) pp. 362​-363​.​ DOI: https://doi.org/10.1002/bimj.201400209 
    ​Details  DOI 
  • 2015 | Journal Article
    ​ ​Expectile and quantile regression-David and Goliath?​
    Waltrup, L. S.; Sobotka, F.; Kneib, T.   & Kauermann, G.​ (2015) 
    Statistical Modelling, 15(5) pp. 433​-456​.​ DOI: https://doi.org/10.1177/1471082X14561155 
    ​Details  DOI  WoS 
  • 2015 | Journal Article | 
    ​ ​Structured Additive Regression Models: An R Interface to BayesX​
    Umlauf, N.; Adler, D.; Kneib, T. ; Lang, S. & Zeileis, A.​ (2015) 
    Journal of Statistical Software, 63(21) pp. 1​-46​.​ DOI: https://doi.org/10.18637/jss.v063.i21 
    ​Details  DOI 
  • 2015 | Journal Article | 
    ​ ​Applying Binary Structured Additive Regression (STAR) for Predicting Wildfire in Galicia, Spain​
    Ríos-Pena, L.; Cadarso-Suárez, C.; Kneib, T.   & Pérez, M.​ (2015) 
    Procedia Environmental Sciences, 27 pp. 123​-126​.​ DOI: https://doi.org/10.1016/j.proenv.2015.07.121 
    ​Details  DOI 
  • 2015 | Journal Article | 
    ​ ​First Nomogram Predicting the Probability of Lymph Node Involvement in Prostate Cancer Patients Undergoing Radioisotope Guided Sentinel Lymph Node Dissection​
    Winter, A.; Kneib, T. ; Rohde, M.; Henke, R.-P. & Wawroschek, F.​ (2015) 
    Urologia Internationalis, 95(4) pp. 422​-428​.​ DOI: https://doi.org/10.1159/000431182 
    ​Details  DOI  PMID  PMC 
  • 2014 | Journal Article
    ​ ​Origin Detection During Food-borne Disease Outbreaks - A Case Study of the 2011 EHEC/HUS Outbreak in Germany​
    Manitz, J. ; Kneib, T. ; Schlather, M.; Helbing, D. & Brockmann, D.​ (2014) 
    PLoS Currents,.​ DOI: https://doi.org/10.1371/currents.outbreaks.f3fdeb08c5b9de7c09ed9cbcef5f01f2 
    ​Details  DOI  PMID  PMC 
  • 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 
  • 2014 | Journal Article | Research Paper | 
    ​ ​A unifying approach to the estimation of the conditional Akaike information in generalized linear mixed models​
    Saefken, B.; Kneib, T. ; van Waveren, C.-S. & Greven, S.​ (2014) 
    Electronic Journal of Statistics, 8(1) pp. 201​-225​.​ DOI: https://doi.org/10.1214/14-EJS881 
    ​Details  DOI 
  • 2014 | Journal Article | 
    ​ ​Spline-based procedures for dose-finding studies with active control​
    Helms, H.-J.; Benda, N.; Zinserling, J.; Kneib, T.   & Friede, T. ​ (2014) 
    Statistics in Medicine, 34(2) pp. 232​-248​.​ DOI: https://doi.org/10.1002/sim.6320 
    ​Details  DOI  PMID  PMC 
  • 2014 | Journal Article | 
    ​ ​A Network-Based Kernel Machine Test for the Identification of Risk Pathways in Genome-Wide Association Studies​
    Freytag, S.; Manitz, J. ; Schlather, M.; Kneib, T. ; Amos, C. I.; Risch, A. & Chang-Claude, J. et al.​ (2014) 
    Human Heredity, 76(2) pp. 64​-75​.​ DOI: https://doi.org/10.1159/000357567 
    ​Details  DOI  PMID  PMC 
  • 2014 | Journal Article
    ​ ​Discussion of "The Evolution of Boosting Algorithms" and "Extending Statistical Boosting"​
    Bühlmann, P.; Gertheiss, J. ; Hieke, S.; Kneib, T. ; Ma, S.; Schumacher, M. & Tutz, G. et al.​ (2014) 
    Methods of Information in Medicine, 53(6) pp. 436​-445​.​ DOI: https://doi.org/10.3414/13100122 
    ​Details  DOI  PMID  PMC  WoS 
  • 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 
  • 2013 | Journal Article
    ​ ​Model building in nonproportional hazard regression​
    Rodríguez-Girondo, M.; Kneib, T. ; Cadarso-Suárez, C. & Abu-Assi, E.​ (2013) 
    Statistics in Medicine, 32(30) pp. 5301​-5314​.​ DOI: https://doi.org/10.1002/sim.5961 
    ​Details  DOI 
  • 2013 | Journal Article
    ​ ​Rejoinder​
    Kneib, T. ​ (2013) 
    Statistical Modelling, 13(4) pp. 373​-385​.​ DOI: https://doi.org/10.1177/1471082X13494531 
    ​Details  DOI  WoS 
  • 2013 | Journal Article | 
    ​ ​Beyond mean regression​
    Kneib, T. ​ (2013) 
    Statistical Modelling, 13(4) pp. 275​-303​.​ DOI: https://doi.org/10.1177/1471082X13494159 
    ​Details  DOI  WoS 
  • 2013 | Journal Article | 
    ​ ​Bayesian semiparametric additive quantile regression​
    Yue, Y. R.; Lang, S.; Flexeder, C.; Waldmann, E.   & Kneib, T. ​ (2013) 
    Statistical Modelling, 13(3) pp. 223​-252​.​ DOI: https://doi.org/10.1177/1471082x13480650 
    ​Details  DOI 
  • 2013 | Journal Article | 
    ​ ​A Novel Kernel for Correcting Size Bias in the Logistic Kernel Machine Test with an Application to Rheumatoid Arthritis​
    Freytag, S.; Bickeböller, H. ; Amos, C. I.; Kneib, T.   & Schlather, M.​ (2013) 
    Human Heredity, 74(2) pp. 97​-108​.​ DOI: https://doi.org/10.1159/000347188 
    ​Details  DOI  PMID  PMC 
  • 2012 | Journal Article
    ​ ​The effect of bark beetle infestation and salvage logging on bat activity in a national park​
    Mehr, M.; Brandl, R.; Kneib, T.   & Müller, J.​ (2012) 
    Biodiversity and Conservation, 21(11) pp. 2775​-2786​.​ DOI: https://doi.org/10.1007/s10531-012-0334-y 
    ​Details  DOI 
  • 2012 | Conference Abstract
    ​ ​Novel Kernel Function in the Logistic Kernel Machine Test for Pathways in GWA Studies​
    Freytag, S.; Amos, C. I.; Bickeböller, H. ; Kneib, T.   & Schlather, M.​ (2012)
    Genetic Epidemiology, 36(7) ​Annual Meeting of the International-Genetic-Epidemiology-Society (IGES)​, Stevenson, WA.
    Hoboken​: Wiley-Blackwell.
    ​Details  WoS 
  • 2011 | Journal Article | 
    ​ ​On confidence intervals for semiparametric expectile regression​
    Sobotka, F.; Kauermann, G.; Schulze Waltrup, L. & Kneib, T. ​ (2011) 
    Statistics and Computing, 23(2) pp. 135​-148​.​ DOI: https://doi.org/10.1007/s11222-011-9297-1 
    ​Details  DOI 

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