Dr. Thorsten Dickhaus
Weierstraß-Institut für Angewandte Analysis und Stochastik Leibniz-Institut im Forschungsverbund Berlin e. V.
Thorsten.Dickhaus@wias-berlin.de
https://www.wias-berlin.de/people/dickhaus/
Themen für das Seminar zur simultanen statistischen Inferenz, SoSe 2014
1. Bayesianische FDR (Bayesian FDR):
Dickhaus, T. (2013). Multiple Testtheorie. Vorlesungsskript, Abschnitt 5.3.
Efron, B., Tibshirani, R. (2002). Empirical Bayes Methods and False Discovery Rates for Microarrays. Genetic Epidemiology 23, 70–86.
2. Bayesianische entscheidungstheoretische multiple Vergleichsprozeduren (Bayesian decision theoretic multiple comparison procedures):
Müller, P., Parmigiani, G., Rice, K. (2007). FDR and Bayesian Multiple Comparisons Rules. In: J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A.
F. M. Smith and M. West (eds.): Bayesian Statistics 8 - Proc. ISBA 8th World Meeting on Bayesian Statistics, Oxford: Oxford University Press, pp. 349–370.
León-Novelo, L.G., Müller, P., Arap, W., Sun, J., Pasqualini, R., Do, K.A. (2013).
Bayesian decision theoretic multiple comparison procedures: An application to phage display data. Biometrical Journal, 55(3), 478–489.
3. Klassifikationstheorie (Einführung) (Introduction to classification theory):
Dickhaus, T. (2014). Simultaneous Statistical Inference with Applications in the Life Sciences. Springer-Verlag Berlin Heidelberg, Chapter 6.
Fahrmeir, L., Hamerle, A, Tutz, G. (eds.). Multivariate statistical methods. 2.,überarb.
Aufl. (Multivariate statistische Verfahren. Unter Mitarbeit von Wolfgang Brachinger, Walter Häußler, Heinz Kaufmann, Peter Kemény, Christian Kredler, Willi Nagl, Friedemann Ost, Heinz Pape.), Berlin: de Gruyter Verlag, 1996, Kapitel 8.
Vapnik, V. N. (1998). Statistical Learning Theory, Adaptive and Learning Systems for Signal Processing, Communications, and Control. Wiley, Chichester.
4. Binäre Klassifikation unter sparsity-Annahmen (Binary classification under sparsity):
Dickhaus, T. (2014). Simultaneous Statistical Inference with Applications in the Life Sciences. Springer-Verlag Berlin Heidelberg, Section 6.1, and references therein.
5. Binäre Klassifikation unter balanciertem Design (Binary classification in non-sparse models):
Dickhaus, T. (2014). Simultaneous Statistical Inference with Applications in the Life Sciences. Springer-Verlag Berlin Heidelberg, Section 6.2, and references therein.
6. Higher Criticism:
Dickhaus, T. (2014). Simultaneous Statistical Inference with Applications in the Life Sciences. Springer-Verlag Berlin Heidelberg, Section 6.3, and references therein.
Gaenssler, P., Stute, W. (1979). Empirical processes: A survey of results for
independent and identically distributed random variables. Ann. Probab. 7, 193-243, and references therein.
7. Modellauswahl (Einführung) (Introduction to model selection):
Leeb, H., Pötscher, B. M. (2009). Model selection. In: Andersen, Torben G. et al.
(eds.): Handbook of financial time series. With a foreword by Robert Engle. Berlin:
Springer-Verlag, and references therein.
8. Konsistente Modellauswahl mit multiplen Testprozeduren (Consistent model selection with multiple test procedures):
Dickhaus, T. (2014). Simultaneous Statistical Inference with Applications in the Life Sciences. Springer-Verlag Berlin Heidelberg, Section 7.1, and references therein.
9. Beziehungen zwischen multiplem Testen und Informationskriterien (Multiple testing and information criteria):
Dickhaus, T. (2014). Simultaneous Statistical Inference with Applications in the Life Sciences. Springer-Verlag Berlin Heidelberg, Section 7.2, and references therein.
10. (Verteilungstheorie für) regularisierte Schätzer (Regularized estimators and their distributions):
Dickhaus, T. (2014). Simultaneous Statistical Inference with Applications in the Life Sciences. Springer-Verlag Berlin Heidelberg, Section 7.3.1, and references therein.
11. Zweistufige Verfahren zur Modellauswahl und –validierung (Two-stage procedures for model selection and validation):
Dickhaus, T. (2014). Simultaneous Statistical Inference with Applications in the Life Sciences. Springer-Verlag Berlin Heidelberg, Section 7.3.2, and references therein.
12. Selektive Inferenz (Selective Inference):
Dickhaus, T. (2014). Simultaneous Statistical Inference with Applications in the Life Sciences. Springer-Verlag Berlin Heidelberg, Section 7.4, and references therein.
