Estimating the accuracy of (local) cross-validation via randomised GCV choices in kernel or smoothing spline regression
نویسندگان
چکیده
منابع مشابه
Smoothing Noisy Data with Spline Functions Estimating the Correct Degree of Smoothing by the Method of Generalized Cross-Validation*
Smoothing splines are well known to provide nice curves which smooth discrete, noisy data. We obtain a practical, effective method for estimating the optimum amount of smoothing from the data. Derivatives can be estimated from the data by differentiating the resulting (nearly) optimally smoothed spline. We consider the model yi=g(ti)+e~, i= 1, 2 . . . . . n, tie[0 , 1], where geW2 ~'~) = {f: j;...
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ژورنال
عنوان ژورنال: Journal of Nonparametric Statistics
سال: 2010
ISSN: 1048-5252,1029-0311
DOI: 10.1080/10485250903095820