\(L_ 1\)-optimal estimates for a regression type function in \(R^ d\)

DOI10.1016/0047-259X(92)90023-9zbMath0744.62064MaRDI QIDQ1185831

Yannis G. Yatracos

Publication date: 28 June 1992

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

zbMATH Keywords

rate of convergenceminimum distance estimationKolmogorov's entropynonparametric regressionempirical measuresL1-consistencysup-norm compact spaceL1-optimal estimatesregression type function

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Order statistics; empirical distribution functions (62G30)

Related Items (3)

Rates of convergence of estimates, Kolmogorov's entropy and the dimensionality reduction principle in regression ⋮ Dependence and the dimensionality reduction principle ⋮ Minimum distance regression-type estimates with rates under weak dependence

Cites Work

• Unnamed Item
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• A regression type problem
• Rates of convergence of minimum distance estimators and Kolmogorov's entropy
• A lower bound on the error in nonparametric regression type problems
• On the estimation of the derivatives of a function with the derivatives of an estimate
• Optimal rates of convergence for nonparametric estimators
• Optimal global rates of convergence for nonparametric regression
• Convergence of estimates under dimensionality restrictions
• Probability Inequalities for Sums of Bounded Random Variables

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