In this paper we investigate the effect of presmoothing on model selection. ChristobalChristobal et al. (1987) showed the beneficial effect of presmoothing for estimating the parameters in a linear regression model. Here, in a regression setting, we show that smoothing the response data prior to...

Variable selection methods and model selection approaches are valuable statistical tools, which are indispensable for almost any statistical modeling question. This review considers first the use of information criteria for model selection. Such criteria provide an ordering of the considered...

We consider the problem of model selection for quantile regression analysis where a particular purpose of the modeling procedure has to be taken into account. Typical examples include estimation of the area under the curve in pharmacokinetics or estimation of the minimum eff ective dose in phase...