Asymptotic properties of nonparametric curve estimates

DOI10.1007/BF01849318zbMath0578.62044MaRDI QIDQ1066585

Ulrich Stadtmüller

Publication date: 1986

Published in: Periodica Mathematica Hungarica (Search for Journal in Brave)

zbMATH Keywords

kernel estimatorslinear estimatorscurve estimatesLILa.s. limit theoremsexact speed of convergencelimit distribution for global deviationnonrandom design pointssmoothed regressograms

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Nonparametric estimation (62G05) Nonparametric tolerance and confidence regions (62G15) General nonlinear regression (62J02) Strong limit theorems (60F15)

Related Items

Kernel approximations of a Wiener process, Nonparametric curve estimation with Bernstein estimates, Shape restricted nonparametric regression with Bernstein polynomials, Strong approximation of maxima by extremal processes, A variable selection approach to monotonic regression with Bernstein polynomials, Approximating moments of continuous functions of random variables using Bernstein polynomials, Variable Neighborhood Programming as a Tool of Machine Learning, A note on generalized Bernstein polynomial density estimators, A Nonparametric Test for Weak Dependence Against Strong Cycles and its Bootstrap Analogue, On confidence bands for multivariate nonparametric regression, Asymptotic properties of Bernstein estimators on the simplex, Asymptotic properties of Dirichlet kernel density estimators, Variable neighborhood programming for symbolic regression, New Entropy Estimator with an Application to Test of Normality, A comparative study of the dose-response analysis with application to the target dose estimation, Nonparametric estimation of a regression function with dependent observations

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• A note on the law of iterated logarithm for weighted sums of random variables
• Extremes and related properties of random sequences and processes
• Smoothing histograms by means of lattice- and continuous distributions
• Approximation of continuous functions by generalized Favard operators
• Consistent nonparametric regression. Discussion
• Contributions to the theory of nonparametric regression, with application to system identification
• On some global measures of the deviations of density function estimates
• Nonparametric Estimation of a Regression Function: Limiting Distribution2
• Matrix Transformations of Weakly Multiplicative Sequences of Random Variables
• Statistical estimation of nonlinear regression functions
• An approximation of partial sums of independent RV's, and the sample DF. II
• Maxima of stationary Gaussian processes
• Asymptotic Properties of the Maximum in a Stationary Gaussian Process
• Curve Estimates
• Nonparametric estimation of a regression function