based on the ideas of mixed models. Specifically, we propose a semiparametric mixed model with boosting to recover the …

inequality constraints on basis coefficients by boosting techniques. Therefore, recently developed componentwise boosting methods …

of the penalized estimator, which is based on a new boosting method, allows to select variables. Real world data and …

variables and the problems of selection of smoothing parameters. Generalized additive model boosting circumvents these problems …

of estimates. The present paper investigates several approaches to combining ridge regression with boosting techniques … the usual ridge estimator. In partial boosting only part of the regression parameters are reestimated within one step of … continuous response variables as well as in the case of generalized linear models. In a simulation study boosting procedures for …

is likelihood based boosting. Boosting originates in the machine learning community where it has been proposed as a … technique to improve classification procedures by combining estimates with reweighted observations. Likelihood based boosting is … a general method which may be seen as an extension of L2 boost. In additive mixed models the advantage of boosting …