Asymptotically optimal selection of a piecewise polynomial estimator of a regression function

DOI10.1016/0047-259X(87)90087-XzbMath0633.62038OpenAlexW2072084563MaRDI QIDQ1096279

Keh-Wei Chen

Publication date: 1987

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0047-259x(87)90087-x

zbMATH Keywords

model selectionasymptotic efficiencymoment conditionsfinal prediction errorfitting piecewise polynomialsFPE-criterion

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Nonparametric estimation (62G05)

Related Items (6)

Optimal global rates of convergence of \(M\)-estimates for multivariate nonparametric regression ⋮ Optimal rates of convergence for the piecewlse polynomial estimator with the index chosen by the fpe selection rule ⋮ Lack-of-fit tests based on weighted ratio of residuals and variances ⋮ Asymptotics of the “minimumL 1-norm” estimates in nonparametric regression models ⋮ On finite-sample properties of adaptive least squares regression estimates ⋮ A Note on the Convergent Rates of M-Estimates for a Partly Linear Model

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