| Conditional variable importance for random forests C Strobl, AL Boulesteix, T Kneib, T Augustin, A Zeileis BMC bioinformatics 9, 1-11, 2008 | 3532 | 2008 |
| Generating survival times to simulate Cox proportional hazards models by Ralf Bender, Thomas Augustin and Maria Blettner, Statistics in Medicine 2005; 24: 1713–1723 R Bender, T Augustin, M Blettner Statistics in medicine 25 (11), 1978-1979, 2006 | 1146* | 2006 |
| Introduction to imprecise probabilities T Augustin, FPA Coolen, G De Cooman, MCM Troffaes John Wiley & Sons, 2014 | 539 | 2014 |
| Unbiased split selection for classification trees based on the Gini index C Strobl, AL Boulesteix, T Augustin Computational Statistics & Data Analysis 52 (1), 483-501, 2007 | 390 | 2007 |
| Nonparametric predictive inference and interval probability T Augustin, FPA Coolen Journal of Statistical Planning and Inference 124 (2), 251-272, 2004 | 209 | 2004 |
| Evaluating microarray-based classifiers: an overview AL Boulesteix, C Strobl, T Augustin, M Daumer Cancer Informatics 6, 2008 | 161 | 2008 |
| Imprecision and prior-data conflict in generalized Bayesian inference G Walter, T Augustin Journal of Statistical Theory and Practice 3 (1), 255-271, 2009 | 76 | 2009 |
| An exact corrected log‐likelihood function for Cox's proportional hazards model under measurement error and some extensions T Augustin Scandinavian Journal of Statistics 31 (1), 43-50, 2004 | 73 | 2004 |
| Imprecise probability. FPA Coolen, MCM Troffaes, T Augustin International encyclopedia of statistical science, 645-648, 2011 | 69 | 2011 |
| A nonparametric predictive alternative to the Imprecise Dirichlet Model: the case of a known number of categories FPA Coolen, T Augustin International Journal of Approximate Reasoning 50 (2), 217-230, 2009 | 68 | 2009 |
| On the impact of robust statistics on imprecise probability models: a review T Augustin, R Hable Structural Safety 32 (6), 358-365, 2010 | 60 | 2010 |
| Learning from multinomial data: a nonparametric predictive alternative to the Imprecise Dirichlet Model. FPA Coolen, T Augustin ISIPTA 5, 125-134, 2005 | 56 | 2005 |
| Powerful algorithms for decision making under partial prior information and general ambiguity attitudes. LV Utkin, T Augustin ISIPTA 5, 349-358, 2005 | 54 | 2005 |
| Concepts for decision making under severe uncertainty with partial ordinal and partial cardinal preferences C Jansen, G Schollmeyer, T Augustin Proceedings of the tenth international symposium on imprecise probability …, 2017 | 51 | 2017 |
| Decision making under incomplete data using the imprecise Dirichlet model LV Utkin, T Augustin International Journal of Approximate Reasoning 44 (3), 322-338, 2007 | 47 | 2007 |
| On the Symbiosis of Two Concepts of Conditional Interval ProbabilityÝ K Weichselberger, T Augustin ISIPTA 3, 606, 2003 | 45 | 2003 |
| Statistical inference T Augustin, G Walter, FPA Coolen Introduction to Imprecise Probabilities, 135-189, 2014 | 43 | 2014 |
| Expected utility within a generalized concept of probability—a comprehensive framework for decision making under ambiguity T Augustin Statistical Papers 43, 5-22, 2002 | 36 | 2002 |
| On Decision Making under Ambiguous Prior and Sampling Information. T Augustin ISIPTA 1, 9-16, 2001 | 36 | 2001 |
| Heaping and its consequences for duration analysis J Wolff, T Augustin Sonderforschungsbereich 386 (203), 1-31, 2000 | 36* | 2000 |
Frank CoolenProfessor of Statistics, Durham UniversityBestätigte E-Mail-Adresse bei durham.ac.uk
