| Conditional variable importance for random forests C Strobl, AL Boulesteix, T Kneib, T Augustin, A Zeileis BMC bioinformatics 9, 1-11, 2008 | 3362 | 2008 |
| Regression models L Fahrmeir, T Kneib, S Lang, B Marx, L Fahrmeir, T Kneib, S Lang, B Marx Regression: Models, methods and applications, 21-72, 2013 | 1312 | 2013 |
| Regressionsmodelle L Fahrmeir, T Kneib, S Lang Regression: Modelle, Methoden und Anwendungen, 19-58, 2007 | 1181 | 2007 |
| Penalized structured additive regression for space-time data: a Bayesian perspective L Fahrmeir, T Kneib, S Lang Statistica Sinica, 731-761, 2004 | 517 | 2004 |
| On the behaviour of marginal and conditional AIC in linear mixed models S Greven, T Kneib Biometrika 97 (4), 773-789, 2010 | 326 | 2010 |
| Software for Bayesian Inference in Structured Additive Regression Models C Belitz, A Brezger, T Kneib, S Lang, EM Fronk, F Heinzl, A Hennerfeind, ... Version, 2012 | 293* | 2012 |
| Bayes X. Software for Bayesian inference based on Markov Chain Monte Carlo simulation techniques A Brezger, T Kneib, S Lang J Stat Software 14, 11, 2005 | 269* | 2005 |
| mboost: Model-based boosting T Hothorn, P Buehlmann, T Kneib, M Schmid, B Hofner R package version 2, 9-1, 2012 | 251 | 2012 |
| Model-based boosting 2.0 T Hothorn, P Bühlmann, T Kneib, M Schmid, B Hofner | 215 | 2010 |
| Generalized additive models for location, scale and shape for high dimensional data—a flexible approach based on boosting A Mayr, N Fenske, B Hofner, T Kneib, M Schmid Journal of the Royal Statistical Society Series C: Applied Statistics 61 (3 …, 2012 | 201 | 2012 |
| Identifying risk factors for severe childhood malnutrition by boosting additive quantile regression N Fenske, T Kneib, T Hothorn Journal of the American Statistical Association 106 (494), 494-510, 2011 | 186 | 2011 |
| Saproxylic beetle assemblages related to silvicultural management intensity and stand structures in a beech forest in Southern Germany J Müller, H Bußler, T Kneib Journal of Insect Conservation 12, 107-124, 2008 | 172 | 2008 |
| Beyond mean regression T Kneib Statistical Modelling 13 (4), 275-303, 2013 | 167 | 2013 |
| Variable selection and model choice in geoadditive regression models T Kneib, T Hothorn, G Tutz Biometrics 65 (2), 626-634, 2009 | 165 | 2009 |
| Structured additive regression models: An R interface to BayesX N Umlauf, D Adler, T Kneib, S Lang, A Zeileis | 163 | 2015 |
| Bayesian structured additive distributional regression with an application to regional income inequality in Germany N Klein, T Kneib, S Lang, A Sohn | 158 | 2015 |
| Bayesian smoothing and regression for longitudinal, spatial and event history data L Fahrmeir, T Kneib Oxford University Press, 2011 | 157 | 2011 |
| Spike-and-slab priors for function selection in structured additive regression models F Scheipl, L Fahrmeir, T Kneib Journal of the American Statistical Association 107 (500), 1518-1532, 2012 | 153 | 2012 |
| Geoadditive expectile regression F Sobotka, T Kneib Computational Statistics & Data Analysis 56 (4), 755-767, 2012 | 152 | 2012 |
| Expectile and quantile regression—David and Goliath? LS Waltrup, F Sobotka, T Kneib, G Kauermann Statistical Modelling 15 (5), 433-456, 2015 | 150 | 2015 |
