Peter L. Bühlmann: Catalogue data in Spring Semester 2018 |
| Name | Prof. Dr. Peter L. Bühlmann |
| Field | Mathematik |
| Address | Seminar für Statistik (SfS) ETH Zürich, HG G 17 Rämistrasse 101 8092 Zürich SWITZERLAND |
| Telephone | +41 44 632 73 38 |
| Fax | +41 44 632 12 28 |
| peter.buehlmann@stat.math.ethz.ch | |
| URL | http://stat.ethz.ch/~peterbu |
| Department | Mathematics |
| Relationship | Full Professor |
| Number | Title | ECTS | Hours | Lecturers | |
|---|---|---|---|---|---|
| 401-3620-18L | Student Seminar in Statistics: Nonparametric Estimation under Shape-Constraints  Number of participants limited to 22. Mainly for students from the Mathematics Bachelor and Master Programmes who, in addition to the introductory course unit 401-2604-00L Probability and Statistics, have heard at least one core or elective course in statistics. | 4 credits | 2S | F. Balabdaoui, P. L. Bühlmann, M. H. Maathuis, N. Meinshausen, S. van de Geer | |
| Abstract | Statistical inference based on a random sample can be performed under additional shape restrictions on the unknown entity to be estimated (regression curve, probability density, ROC curve...). Under shape restrictions, we mean a variety of constraints. Examples thereof include monotonicity, bounded variation, convexity, k-monotonicity or log-concavity. | ||||
| Learning objective | The main goal of this Student Seminar is to get acquainted with the existing approaches in shape constrained estimation. The students will get to learn that specific estimation techniques can be used under shape restrictions to obtain better estimators, especially for small/moderate sample sizes. Students will also have the opportunity to learn that one of the main merits of shape constrained inference is to avoid choosing some arbitrary tuning parameter as it is the case with bandwidth selection in kernel estimation methods. Furthemore, students will get to read about some efficient algorithms that can be used to fastly compute the obtained estimators. One of the famous algoritms is the so-called PAVA (Pool Adjacent Violators Algorithm) used under monotonicity to compute a monotone estimator of a regression curve or a probability density. During the Seminar, the students will have to study some selected chapters from the books "Statistical Inference under Order Restrictions" by Barlow, Bartholomew, Bremner and Brunk, and "Nonparametric estimation under shape constraints" by Groeneboom and Jongbloed. Some "famous" articles on the subject will be also studied. | ||||
| Prerequisites / Notice | We require at least one course in statistics in addition to the 4th semester course Introduction to Probability and Statistics and basic knowledge in computer programming. Topics will be assigned during the first meeting. | ||||
| 401-3622-00L | Regression | 8 credits | 4G | P. L. Bühlmann | |
| Abstract | In regression, the dependency of a random response variable on other variables is examined. We consider the theory of linear regression with one or more covariates, high-dimensional linear models, nonlinear models and generalized linear models, robust methods, model choice and nonparametric models. Several numerical examples will illustrate the theory. | ||||
| Learning objective | Introduction into theory and practice of a broad and popular area of statistics, from a modern viewpoint. | ||||
| Content | In der Regression wird die Abhängigkeit einer beobachteten quantitativen Grösse von einer oder mehreren anderen (unter Berücksichtigung zufälliger Fehler) untersucht. Themen der Vorlesung sind: Einfache und multiple Regression, Theorie allgemeiner linearer Modelle, Hoch-dimensionale Modelle, Ausblick auf nichtlineare Modelle. Querverbindungen zur Varianzanalyse, Modellsuche, Residuenanalyse; Einblicke in Robuste Regression. Durchrechnung und Diskussion von Anwendungsbeispielen. | ||||
| Lecture notes | Lecture notes | ||||
| Prerequisites / Notice | Credits cannot be recognised for both courses 401-3622-00L Regression and 401-0649-00L Applied Statistical Regression in the Mathematics Bachelor and Master programmes (to be precise: one course in the Bachelor and the other course in the Master is also forbidden). | ||||
| 401-5000-00L | Zurich Colloquium in Mathematics  | 0 credits | P. L. Bühlmann, A. Iozzi, S. Mishra, R. Pandharipande, University lecturers | ||
| Abstract | The lectures try to give an overview of "what is going on" in important areas of contemporary mathematics, to a wider non-specialised audience of mathematicians. | ||||
| Learning objective | |||||
| 401-5620-00L | Research Seminar on Statistics | 0 credits | 2K | P. L. Bühlmann, L. Held, T. Hothorn, D. Kozbur, M. H. Maathuis, N. Meinshausen, M. Wolf | |
| Abstract | Research colloquium | ||||
| Learning objective | |||||
| 401-5640-00L | ZüKoSt: Seminar on Applied Statistics | 0 credits | 1K | M. Kalisch, P. L. Bühlmann, R. Furrer, L. Held, T. Hothorn, M. H. Maathuis, M. Mächler, L. Meier, N. Meinshausen, M. Robinson, C. Strobl | |
| Abstract | 5 to 6 talks on applied statistics. | ||||
| Learning objective | Kennenlernen von statistischen Methoden in ihrer Anwendung in verschiedenen Gebieten, besonders in Naturwissenschaft, Technik und Medizin. | ||||
| Content | In 5-6 Einzelvorträgen pro Semester werden Methoden der Statistik einzeln oder überblicksartig vorgestellt, oder es werden Probleme und Problemtypen aus einzelnen Anwendungsgebieten besprochen. 3 bis 4 der Vorträge stehen in der Regel unter einem Semesterthema. | ||||
| Lecture notes | Bei manchen Vorträgen werden Unterlagen verteilt. Eine Zusammenfassung ist kurz vor den Vorträgen im Internet unter http://stat.ethz.ch/talks/zukost abrufbar. Ankündigunen der Vorträge werden auf Wunsch zugesandt. | ||||
| Prerequisites / Notice | Dies ist keine Vorlesung. Es wird keine Prüfung durchgeführt, und es werden keine Kreditpunkte vergeben. Nach besonderem Programm. Koordinator M. Kalisch, Tel. 044 632 3435 Lehrsprache ist Englisch oder Deutsch je nach ReferentIn. Course language is English or German and may depend on the speaker. | ||||