Nonparametric Kernel Regression Estimation-Optimal Choice of Bandwidth

DOI10.1080/02331888708801986zbMath0622.62043OpenAlexW2020666770MaRDI QIDQ3759718

Gabrielle Kelly, Wolfgang Karl Härdle

Publication date: 1987

Published in: Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331888708801986

zbMATH Keywords

optimal bandwidthhigher momentskernel regression estimatorschoice of smoothing parameterautomatic smoothingestimation of regression surfaces

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05)

Related Items (6)

Growth curves: A two-stage nonparametric approach ⋮ Order Choice in Nonlinear Autoregressive Models ⋮ Bandwidth choice for nonparametric classification ⋮ Editorial to the special issue on applicable semiparametrics of computational statistics ⋮ Understanding past ocean circulations: a nonparametric regression case study ⋮ Semiparametric estimates and tests of base-independent equivalence scales

Cites Work

• Bandwidth choice for nonparametric regression
• Optimal bandwidth selection in nonparametric regression function estimation
• An asymptotically optimal window selection rule for kernel density estimates
• Probabilities of maximal deviations for nonparametric regression function estimates
• Optimal global rates of convergence for nonparametric regression
• Statistical predictor identification
• Asymptotic properties of integrated square error and cross-validation for kernel estimation of a regression function
• Probability Inequalities for Sums of Bounded Random Variables
• A new look at the statistical model identification

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