Model Selection in Linear Mixed Models Using Mdl Criterion with an Application to Spline Smoothing
نویسندگان
چکیده
For spline smoothing one can rewrite the smooth estimation as a linear mixed model (LMM) where the smoothing parameter appears as the variance of spline basis coefficients. Smoothing methods that use basis functions with penalization can utilize maximum likelihood (ML) theory in LMM framework ([8]). We introduce the minimum description length (MDL) model selection criterion in LMM and propose an automatic data-based spline smoothing method based on the MDL criterion.
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