Abstract
Abstract This article describes an appropriate way of implementing the generalized cross-validation method and some other least-squares-based smoothing parameter selection methods in penalized likelihood regression problems, and explains the rationales behind it. Simulations of limited scale are conducted to back up the semitheoretical analysis.
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