Search Results - subject:"Likelihood-based boosting"

Multinomial logit models with implicit variable selection

Zahid, Faisal; Tutz, Gerhard - In: Advances in Data Analysis and Classification 7 (2013) 4, pp. 393-416

The multinomial logit model is the most widely used model for the unordered multi-category responses. However, applications are typically restricted to the use of few predictors because in the high-dimensional case maximum likelihood estimates frequently do not exist. In this paper we are...

Persistent link: https://www.econbiz.de/10010728111

Variable selection and model choice in structured survival models

Hofner, Benjamin; Hothorn, Torsten; Kneib, Thomas - In: Computational Statistics 28 (2013) 3, pp. 1079-1101

fitting that enables simultaneous variable selection and model choice. We introduce a component-wise, likelihood-based … boosting algorithm for survival data that permits the inclusion of both parametric and nonparametric time-varying effects as …

Persistent link: https://www.econbiz.de/10010847731

Generalized smooth monotonic regression

Tutz, Gerhard; Leitenstorfer, Florian - 2005

functions a likelihood based boosting algorithm is proposed which is simply to implement. Stopping criteria and inference are …

Persistent link: https://www.econbiz.de/10010266140