Talks and Poster Presentations (with Proceedings-Entry):
S. Serneels, P. Filzmoser, I. Hoffmann, C. Croux:
"Sparse partial robust M regression";
Talk: ICORS2014 - 14th International Conference on Robust Statistics 2014,
Martin-Luther-Universität Halle-Wittenberg, D;
2014-08-10
- 2014-08-15; in: "ICORS14 - Conference Guide & Book of Abstracts",
(2014),
24.
English abstract:
Sparse partial robust M regression is introduced as a new regression method. It is
the first dimension reduction and regression algorithm that yields estimates with a partial least
squares alike interpretability that are both sparse and robust with respect to vertical outliers
and leverage points. Comparisons with the classical counterpart Sparse Partial Least Squares
(SPLS) regression (Chun & Keles, 2010), as well as to the non-sparse counterparts are made
(Serneels et al., 2005).
Keywords:
partial least squares regression sparse regression high-dimensional data
Electronic version of the publication:
http://statistik.wiwi.uni-halle.de/icors2014/
Created from the Publication Database of the Vienna University of Technology.