| Conditional variable importance for random forests C Strobl, AL Boulesteix, T Kneib, T Augustin, A Zeileis BMC bioinformatics 9 (1), 307, 2008 | 1576 | 2008 |
| Regression L Fahrmeir, T Kneib, S Lang, B Marx Springer-Verlag Berlin Heidelberg, 2007 | 726 | 2007 |
| Regression models L Fahrmeir, T Kneib, S Lang, B Marx Regression, 21-72, 2013 | 565 | 2013 |
| Penalized structured additive regression for space-time data: a Bayesian perspective L Fahrmeir, T Kneib, S Lang Statistica Sinica, 731-761, 2004 | 399 | 2004 |
| mboost: Model-based boosting T Hothorn, P Bühlmann, T Kneib, M Schmid, B Hofner R package version, 2.1-2, 2012 | 221 | 2012 |
| On the behaviour of marginal and conditional AIC in linear mixed models S Greven, T Kneib Biometrika 97 (4), 773-789, 2010 | 202 | 2010 |
| BayesX: Analysing Bayesian structured additive regression models A Brezger, T Kneib, S Lang Discussion paper//Sonderforschungsbereich 386 der Ludwig-Maximilians …, 2003 | 190 | 2003 |
| BayesX-Software for Bayesian inference in structured additive regression models C Belitz, A Brezger, T Kneib, S Lang, N Umlauf Version 2 (1), 2009 | 184* | 2009 |
| Model-based boosting 2.0 T Hothorn, P Bühlmann, T Kneib, M Schmid, B Hofner Journal of Machine Learning Research 11 (Aug), 2109-2113, 2010 | 139 | 2010 |
| 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 | 123 | 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 (2), 107, 2008 | 119 | 2008 |
| A mixed model approach for geoadditive hazard regression T Kneib, L Fahrmeir Scandinavian Journal of Statistics 34 (1), 207-228, 2007 | 119 | 2007 |
| Variable selection and model choice in geoadditive regression models T Kneib, T Hothorn, G Tutz Biometrics 65 (2), 626-634, 2009 | 118 | 2009 |
| 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 …, 2012 | 115 | 2012 |
| Structured additive regression for categorical space–time data: A mixed model approach T Kneib, L Fahrmeir Biometrics 62 (1), 109-118, 2006 | 111 | 2006 |
| Simultaneous confidence bands for penalized spline estimators T Krivobokova, T Kneib, G Claeskens Journal of the American Statistical Association 105 (490), 852-863, 2010 | 107 | 2010 |
| Bayesian smoothing and regression for longitudinal, spatial and event history data L Fahrmeir, T Kneib OUP Catalogue, 2011 | 104 | 2011 |
| Influence of brain-derived neurotrophic-factor and apolipoprotein E genetic variants on hippocampal volume and memory performance in healthy young adults T Richter-Schmidinger, P Alexopoulos, M Horn, S Maus, M Reichel, ... Journal of neural transmission 118 (2), 249-257, 2011 | 102 | 2011 |
| Geoadditive expectile regression F Sobotka, T Kneib Computational Statistics & Data Analysis 56 (4), 755-767, 2012 | 90 | 2012 |
| Analysis of the individual and aggregate genetic contributions of previously identified serine peptidase inhibitor Kazal type 5 (SPINK5), kallikrein-related peptidase 7 (KLK7 … S Weidinger, H Baurecht, S Wagenpfeil, J Henderson, N Novak, ... Journal of allergy and clinical immunology 122 (3), 560-568. e4, 2008 | 86 | 2008 |
