Asymptotic comparison of (partial) cross-validation, GCV and randomized GCV in nonparametric regression

DOI10.1214/aos/1030563988zbMath0932.62047OpenAlexW1990751459MaRDI QIDQ1807078

Didier A. Girard

Publication date: 9 November 1999

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/aos/1030563988

zbMATH Keywords

regularizationcross-validationbandwidth selectionnonparametric regressiongeneralized cross-validationfast randomized versions of GCVpartial cross-validation

Mathematics Subject Classification ID

Related Items (11)

On the excess of average squared error for data-driven bandwidths in nonparametric trend estimation ⋮ Stochastic approximation of score functions for Gaussian processes ⋮ Local adaptive smoothing in kernel regression estimation ⋮ Model building with likelihood basis pursuit ⋮ Bootstrap bandwidth selection method for local linear estimator in exponential family models ⋮ A survey of cross-validation procedures for model selection ⋮ Estimating the accuracy of (local) cross-validation via randomised GCV choices in kernel or smoothing spline regression ⋮ On bandwidth selection problems in nonparametric trend estimation under martingale difference errors ⋮ Copula Density Estimation by Total Variation Penalized Likelihood ⋮ Parameter Choices for Fast Harmonic Spline Approximation ⋮ Smoothing spline ANOVA models for large data sets with Bernoulli observations and the randomized GACV.

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