Statistics Seminar: Irene Gijbels (KU Leuven) -- Robust estimation and variable selection in linear regression

Notes:
* Talk is on Thursday, not the usual Friday.
* Talk in the AGR, not Carslaw 173

Abstract: 

In this talk the interest is in robust procedures to select variables in a 
multiple linear regression modeling context. Throughout the talk the focus 
is on how to adapt the non-negative garrote selection method to get to a 
robust variable selection method. We establish estimation and variable 
selection consistency properties of the developed method, and discuss 
robustness properties such as breakdown point and influence function. In a 
second part of the talk the focus is on heteroscedastic linear regression 
models, in which one also wants to select the variables that influence the 
variance part. Methods for robust estimation and variable selection are 
discussed, and illustrations of their influence functions are provided. 
Throughout the talk examples are given to illustrate the practical use of 
the methods.