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Cross-Validating Non-Gaussian Data
Authors:Chong Gu
Institution:Department of Statistics , Purdue University , West Lafayette , IN , 47907 , USA
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.
Keywords:Generalized cross-validation  Performance-oriented iteration  Pseudodata  Smoothing parameter  Unbiased risk estimate
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