Anwendungsgebiete
Übersicht
Sozialwissenschaften
- Luisa Ebner, Patrick Schwaferts, and Thomas Augustin. Robust Bayes factor for independent two-sample comparisons under imprecise prior information. In Jasper De Bock, Cassio P. de Campos, Gert de Cooman, Erik Quaeghebeur, and Gregory Wheeler, editors, Proceedings of the Eleventh International Symposium on Imprecise Probability: Theories and Applications, volume 103 of Proceedings of Machine Learning Research, pages 167–174. PMLR, 2019. (PDF)
- Aziz Omar and Thomas Augustin. Estimation of classification probabilities in small domains accounting for nonresponse relying on imprecise probability. International Journal of Approximate Reasoning, 115:134–143, 2019. Substantially extended, invited special issue version of Omar & Augustin (2018, SMPS).
- Patrick Schwaferts and Thomas Augustin. Imprecise hypothesis-based Bayesian decision making with simple hypotheses. In Jasper De Bock, Cassio P. de Campos, Gert de Cooman, Erik Quaeghebeur, and Gregory Wheeler, editors, Proceedings of the Eleventh International Symposium on Imprecise Probability: Theories and Applications, volume 103 of Proceedings of Machine Learning Research, pages 338–345. PMLR, 2019. (PDF)
- Christoph Jansen. Some contributions to decision making in complex information settings with imprecise probabilities and incomplete preferences: Theoretical and algorithmic results. PhD thesis, Department of Statistics, LMU Munich, 2018.
- Aziz Omar and Thomas Augustin. Estimation of classification probabilities in small domains accounting for nonresponse relying on imprecise probability. In Sebastien Destercke, Thierry Denoeux, Maria Angeles Gil, Przemyslaw Grzegorzewski, and Olgierd Hryniewicz, editors, SMPS 2018: Uncertainty Modelling in Data Science, volume 832 of Advances in Intelligent Systems and Computing, pages 175–182. Springer, 2018.
- Julia Plass. Statistical modelling of categorical data under ontic and epistemic imprecision: contributions to power set based analyses, cautious likelihood inference and (non-)testability of coarsening mechanism. PhD thesis, Department of Statistics, LMU Munich, 2018.
- Julia Plass, Marco Cattaneo, Thomas Augustin, Georg Schollmeyer, and Christian Heumann. Towards a reliable categorical regression analysis for non-randomly coarsened observations: An analysis with German labour market data. Technical Report 206, Department of Statistics, LMU Munich, 2017.
- Julia Plass, Aziz Omar, and Thomas Augustin. Towards a cautious modelling of missing data in small area estimation. In Alessandro Antonucci, Giorgio Corani, Inés Couso, and Sébastien Destercke, editors, Proceedings of the Tenth International Symposium on Imprecise Probability: Theories and Applications, volume 62 of Proceedings of Machine Learning Research, pages 253–264. PMLR, 2017.
- Julia Plass, Aziz Omar, and Thomas Augustin. Towards a cautious modelling of missing data in small area estimation. In Alessandro Antonucci, Giorgio Corani, Inés Couso, and Sébastien Destercke, editors, Proceedings of the Tenth International Symposium on Imprecise Probability: Theories and Applications, volume 62 of Proceedings of Machine Learning Research, pages 253–264. PMLR, 2017.
- Julia Kopf, Thomas Augustin, and Carolin Strobl. The potential of model-based recursive partitioning in the social sciences — Revisiting Ockham's Razor. In John McArdle and Gilbert Ritschard, editors, Contemporary Issues in Exploratory Data Mining, pages 75–95. Routledge, New York, 2013.
- Christoph Wunder, Andrea Wiencierz, Johannes Schwarze, and Helmut Küchenhoff. Well-being over the life span: Semiparametric evidence from British and German longitudinal data. Review of Economics and Statistics, 95:154–167, 2013.
- Daniel Fischer, Wolfgang Bonß, Thomas Augustin, Felix Bader, Michaela Pichlbauer, and Dominikus Vogl, editors. Uneindeutigkeit als Herausforderung. Universität der Bundeswehr München, Neubiberg, 1 edition, 2011.
- Julia Kopf, Thomas Augustin, and Carolin Strobl. The potential of model-based recursive partitioning in the social sciences — Revisiting Ockham's Razor. Technical Report 88, Department of Statistics, LMU Munich, 2010.
Psychometrie
Bisher keine Veröffentlichungen in diesem Bereich
Biostatistik
- Cornelia Fuetterer and Thomas Augustin. Internal validation of unsupervised clustering following an association accuracy heuristic. In IEEE International Conference on Bioinformatics and Biomedicine (BIBM): Workshop on Machine Learning and Artificial Intelligence in Bioinformatics and Medical Informatics (MABM 2021), pages 2201–2210, 2021. (doi:10.1109/BIBM52615.2021.9669782)
- Cornelia Fütterer, Malte Nalenz, and Thomas Augustin. Discriminative power Lasso – incorporating discriminative power of genes into regularization-based variable selection. 2021. Technical Report. Available under: https://epub.ub.uni-muenchen.de/77862.
- Cornelia Fuetterer, Thomas Augustin, and Christiane Fuchs. Adapted single-cell consensus clustering (adasc3). Advances in Data Analysis and Classification, 2020.
- Cornelia Fuetterer, Georg Schollmeyer, and Thomas Augustin. Constructing simulation data with dependency structure for unreliable single-cell rna-sequencing data using copulas. In Jasper De Bock, Cassio P. de Campos, Gert de Cooman, Erik Quaeghebeur, and Gregory Wheeler, editors, Proceedings of the Eleventh International Symposium on Imprecise Probabilities: Theories and Applications, volume 103 of Proceedings of Machine Learning Research, pages 216–224, Thagaste, Ghent, Belgium, 03–06 Jul 2019. PMLR. (PDF)
- Hansjörg Baurecht, Melanie Hotze, Elke Rodríguez, Judith Manz, Stephan. Weidinger, Heather J. Cordell, Thomas Augustin*, and Konstantin Strauch*. (*equal contr.) Compare and contrast meta analysis (CCMA): A method for identification of pleiotropic loci in genome-wide association studies. PLoS ONE, 11:1–10, 5 2016.
- Xavier Blanchet, Katja Cesarek, Johanna Brandt, Heiko Herwald, Daniel Teupser, Helmut Küchenhoff, Ela Karshovska, Sebastian F. Mause, Wolfgang Siess, Hermann Wasmuth, Oliver Soehnlein, Rory R. Koenen, Christian Weber, and Philipp von Hundelshausen. Inflammatory role and prognostic value of platelet chemokines in acute coronary syndrome. Thrombosis and Haemostasis, 112(6):1277–1287, 2014.
- Eva Endres. Pre-validation for assessing the added predictive value of high-dimensional molecular data in binary classification. Master's thesis, LMU Munich, 2014.
- Matthias Schmid, Thomas Hielscher, Thomas Augustin, and Olaf Gefeller. A robust alternative to the Schemper-Henderson measure of prediction error. Biometrics, 67(2):524–535, 2011.
- David Rummel, Thomas Augustin, and Helmut Küchenhoff. Correction for covariate measurement error in nonparametric longitudinal regression. Biometrics, 66(4):1209–1219, 2010.
- Thomas Augustin, Angela Döring, and David Rummel. Regression calibration for Cox regression under heteroscedastic measurement error — Determining risk factors of cardiovascular diseases from error-prone nutritional replication data. In Christian Heumann and Shalabh, editors, Recent Advances in Linear Models and Related Areas, Essays in Honour of Helge Toutenburg, pages 253–278. Physika Verlag, Heidelberg, 2008.
- Ralf Bender, Thomas Augustin, and Maria Blettner. Generating survival times to simulate Cox proportional hazards models. Statistics in Medicine, 24(11):1713–1723, 2005.
Survey Statistik
- Dominik Kreiss, Georg Schollmeyer, and Thomas Augustin. Towards improving electoral forecasting by including undecided voters and interval-valued prior knowledge. In Proceedings of the Twelfth International Symposium on Imprecise Probabilities: Theories and Applications, Proceedings of Machine Learning Research, Granada, Spain, 06–09 Jul 2021.
- Patrick Schwaferts and Thomas Augustin. Imprecise hypothesis-based bayesian decision making with composite hypotheses. In Proceedings of the Twelfth International Symposium on Imprecise Probabilities: Theories and Applications, Proceedings of Machine Learning Research, Granada, Spain, 06–09 Jul 2021.
- Dominik Kreiss and Thomas Augustin. Undecided voters as set-valued information, towards forecasts under epistemic imprecision. In Jesse Davis and Karim Tabia, editors, Scalable Uncertainty Management 2020, pages 242–250. Springer, 2020.
- Dominik Kreiss, Malte Nalenz, and Thomas Augustin. Undecided voters as set-valued information, machine learning approaches under complex uncertainty. In Eyke Huellermeier and Sebastian Destercke, editors, ECML/PKDD 2020 Tutorial and Workshop on Uncertainty in Machine Learning. 2020.
- Eva Endres, Paul Fink, and Thomas Augustin. Imprecise imputation: A nonparametric micro approach reflecting the natural uncertainty of statistical matching with categorical data. Journal of Official Statistical, 35:599–624, 2019.
- Aziz Omar and Thomas Augustin. Estimation of classification probabilities in small domains accounting for nonresponse relying on imprecise probability. International Journal of Approximate Reasoning, 115:134–143, 2019. Substantially extended, invited special issue version of Omar & Augustin (2018, SMPS).
- Julia Plass, Marco Cattaneo, Thomas Augustin, Georg Schollmeyer, and Christian Heumann. Reliable inference in categorical regression analysis for non-randomly coarsened observations. International Statistical Review, 87:580–603, 2019.
- Aziz Omar and Thomas Augustin. Estimation of classification probabilities in small domains accounting for nonresponse relying on imprecise probability. In Sebastien Destercke, Thierry Denoeux, Maria Angeles Gil, Przemyslaw Grzegorzewski, and Olgierd Hryniewicz, editors, SMPS 2018: Uncertainty Modelling in Data Science, volume 832 of Advances in Intelligent Systems and Computing, pages 175–182. Springer, 2018.
- Julia Plass, Aziz Omar, and Thomas Augustin. Towards a cautious modelling of missing data in small area estimation. In Alessandro Antonucci, Giorgio Corani, Inés Couso, and Sébastien Destercke, editors, Proceedings of the Tenth International Symposium on Imprecise Probability: Theories and Applications, volume 62 of Proceedings of Machine Learning Research, pages 253–264. PMLR, 2017.