文章基本信息

标题：Asymptotic Properties of Generalized Cross Validation Estimators for Regularized System Identification ⁎
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作者：Biqiang Mu ; Tianshi Chen ; Lennart Ljung 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2018
卷号：51
期号：15
页码：203-208
DOI：10.1016/j.ifacol.2018.09.130
语种：English
出版社：Elsevier
摘要：AbstractIn this paper, we study the asymptotic properties of the generalized cross validation (GCV) hyperparameter estimator and establish its connection with the Stein’s unbiased risk estimators (SURE) as well as the mean squared error (MSE). It is shown that as the number of data goes to infinity, the GCV has the same asymptotic property as the SURE does and both of them converge to the best hyperparameter in the MSE sense. We illustrate the efficacy of the result by Monte Carlo simulations.
关键词：KeywordsRegularized system identificationGeneralized cross-validationStein’s unbiased risk estimatorsAsymptotic analysis