Andreas Groll (Dipl.-Mathematiker)

Wissenschaftlicher Mitarbeiter

Variable Selection for Generalized Linear Mixed Models by L1-Penalized Estimation,
CEN, 12.-15. September 2011, Zürich, Schweiz.
Variable Selection for Generalized Additive Mixed Models by Likelihood-based Boosting,
AMSDA, 07.-10. Juni 2011, Rom, Italien.
Ordinal Random Effects Models Including Vatiable Selection,
BioMed-S Retreat, 22.-23. Juli 2010, Höhenried, Deutschland.
Variable Selection in Generalizde Mixed Models,
DAGStat, 23.-26. März 2010, Dortmund, Deutschland.
Generalized Additive Mixed Models based on boosting,
DStatG NAchwuchsworkshop, 3.-5. Juni 2009, Merseburg, Deutschland.

Rubenbauer, S., A. Groll, and F. Leitenstorfer. An improved bootstrap methodology for the estimation of predictive claim reserve distributions. Submitted.
Tutz, G. and A. Groll (2010): Generalized Linear Mixed Models Based on Boosting. In T. Kneib and G. Tutz (Eds.), Statistical Modelling and Regression Structures - Festschrift in the Honour of Ludwig Fahrmeir, Physica.
Tutz, G. and A. Groll (2011): Likelihood-based Boosting in Binary and Ordinal Random Effects Models. Under revision.
Groll, A. and G. Tutz (2011): Variable selection for generalized additive mixed models by likelihood-based boosting. In Organizing Commitee (Ed.), Proceedings ASMDA 2011. Sapienza Università di Roma.
Groll, A. and G. Tutz (2011): Regularization for generalized additive mixed models by likelihood-based boosting. To appear.
Groll, A. and G. Tutz (2011): Variable selection for generalized linear mixed models by L1-penalized estimation. Submitted.

Testversion R-package für Boosting in GMMs: GMMBoost; bald auch erhältlich auf CRAN.
Testversion R-package für Variablenselektion im generalisierten linearen gemischten Model mittels L1-Penalisierung: glmmLasso; bald auch erhältlich auf CRAN.