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Dr. Martin Maechler, Prof. Peter Bühlmann | Lectures: Th 13-15, HG G 3, Fr 9-10, HG G 3 |
Tutors: Alain Hauser, Fabio Sigrist, Jonas Peters |
Exercises: Fr 10-12, HG G 3 Exceptions: Fr 24.02. 10-12, HG E 26.1 and HG E 26.3 |
Multiple
regression, nonparametric methods for regression and classification
(kernel estimates, smoothing splines, regression and classification
trees, additive models, projection pursuit, neural nets), curse of
dimensionality, resampling, bootstrap, cross validation.
(more details: Course Catalogue Data)
Thursday, 23.02.2012 (Exercises start on 24.02. with a special introduction to the "R" software)
A selection is online in this ftp directory.
Exercises will be based on the free open-source statistics and graphics software R. Emphasis will be put on applied problems. Active participation in the exercises is strongly recommended for all.
Of course you can always ask questions during the class and the exercise sessions. If you want to contact us by email, please write to compstat@stat.math.ethz.ch, NOT directly to a tutor.
In order to obtain ETCS-credits you have to pass the written exam.
If you need ETH-credits you need to hand in your exercises and achieve a minimal amount of 40 points. (see the exercise page for more details)
T. Hastie, R. Tibshirani, J. Friedman. The Elements of Statistical Learning. Springer
J. E. Gentle. Elements of Computational Statistics. Springer
W. N. Venables, B. D. Ripley. Modern Applied Statistics with S. Springer
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