On a class of nonparametric density and regression estimators

DOI10.1214/aos/1176346791zbMath0586.62051OpenAlexW1972574026MaRDI QIDQ1071427

V. K. Klonias

Publication date: 1984

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

Full work available at URL: https://doi.org/10.1214/aos/1176346791

zbMATH Keywords

consistencynumerical examplesgraphsoptimal rates of convergenceSobolev normsHellinger metricdensity estimatesregression estimatorsdata based choice of the smoothing parametergeneral roughness-penalty functionalmaximum penalized likelihood estimatorsnew spline estimates

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Nonparametric estimation (62G05) Strong limit theorems (60F15) Rate of convergence, degree of approximation (41A25) Spline approximation (41A15) (L^p)-limit theorems (60F25)

Related Items (8)

Discriminant analysis and density estimation on the finite d-dimensional grid ⋮ Numerical techniques in nonparametric estimation† ⋮ Estimation of the reciprocal of the density quantile function at a point ⋮ A penalty method for nonparametric estimation of the intensity function of a counting process ⋮ Maximum penalized likelihood estimation and smoothed em algorithms for positive integral equatioins of the first kind ⋮ Density estimation under the koziol‐green model of censoring by penalized likelihood methods ⋮ Nonparametric Functional Estimation by Asymptotic Regression ⋮ Optimal convergence rates for Good's nonparametric maximum likelihood density estimator

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