Smoothing methods that use basis functions with penalization can be formulated as fits in formlinear mixed effects models. This allows s uch models to be fitted using sta ndard mixed models structures. In this paper we provide an estimation and inference for linear mixed models using restrict- ed maximum likelihood and penalized spline smoothing, and describe the connection between the two. To this end, a real data example is considered and model is fitted in R using diff erent package. We see that penalized spline smoothing expressed in form of linear mixed model gives the better results than standard mixed effects model.
Karma etkili model Yarı-parametrik regresyon Cezalı splayn düzeltme parametresi Genelleştirilmiş çapraz geçerlilik
Primary Language | English |
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Journal Section | Articles |
Authors | |
Publication Date | May 6, 2015 |
Published in Issue | Year 2013 Volume: 2 Issue: 2 |