LFU:online

Institut für Statistik Institut für Statistik

Dr. Torsten Hothorn Dr. Torsten Hothorn
Dr. Thomas Kneib Dr. Thomas Kneib

403903

KU Statistik

KU 1

2,5

Block

jährlich

Englisch

Knowledge in advanced statistics

Termin 1: Spatial Statistics with R: Prof. Dr. Thomas Kneib (Uni Göttingen). 7. März 2013: Spatial Statistics is concerned with the analysis and regression modelling of data that are spatially aligned, where spatial information can be given in different form, for example in terms of exact coordinates or vie regional information. In other applications, the location of points in space is of interest in its own right. Depending on the specific data structure available, different specialized solutions from spatial statistics have to be considered. Within this course, we will deal with spatial statistics methods and their implementation in R. More specifically, the course will cover the following subjects: • Geostatistical approaches based on stationary Gaussian random fields. • Markov random fields for analyzing regional spatial data. • Statistical methods for the analysis of spatial point patterns. All contents of the course will be illustrated in worked examples. Prerequisites: Solid background knowledge on linear models, experience in statistical analyses and programming with R. Termin 2: Prof. Dr. Torsten Hothorn (Uni Zürich): 25./26. Juni 2013: Model-based Boosting in R: We provide a detailed hands-on tutorial for the R add-on package mboost. The package implements boosting for optimizing general risk functions utilizing component-wise (penalized) least squares estimates as base-learners for fitting various kinds of generalized linear and generalized additive models to potentially high-dimensional data. We give a theoretical background and demonstrate how mboost can be used to t interpretable models of different complexity. The package is illustrated by a number of case studies from different domains.

Updated information will be available at the corresponding OLAT course.

Updated information will be available at the corresponding OLAT course.

Termin 1: - Diggle & Ribeiro (2007): Model-based geostatistics, Springer - Illian, Penttinen, Stoyan & Stoyan (2008). Statistical Analysis and Modelling of Spatial Point Patterns. Wiley. - Rue & Held (2005): Gaussian Markov Random Fields, Chapman & Hall / CRC. Termin 2: The course material is partially based on Hofner et al. (2012). Benjamin Hofner, Andreas Mayr, Nikolay Robinzonov and Mattthias Schmid (2012), Model-based Boosting in R - A Hands-on Tutorial Using the R Package mboost. Computational Statistics; http://dx.doi.org/10.1007/s00180-012-0382-5.

Updated information will be available at the corresponding OLAT course.
Beginn: 7.03.2013