Chung--Smirnov property for perturbed empirical distribution functions

DOI10.1016/0167-7152(93)90152-9zbMath0778.62031OpenAlexW2077705376MaRDI QIDQ1209460

H. J. A. Degenhardt

Publication date: 16 May 1993

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-7152(93)90152-9

zbMATH Keywords

kernel smoothingempirical processeskernel density estimatorslaws of iterated logarithmChung-Smirnov propertyintegrals of kernel functionsnew convergence criteria

Mathematics Subject Classification ID

Density estimation (62G07) Order statistics; empirical distribution functions (62G30)

Related Items (6)

The laws of the iterated logarithm for two kinds of PP statistics ⋮ Necessary and sufficient conditions for weak convergence of smoothed empirical processes. ⋮ Chung-Smirnov property for smoothed distribution function estimator under random censorship ⋮ On the smoothed bootstrap ⋮ Chung–Smirnov property for Bernstein estimators of distribution functions ⋮ A New Kernel Distribution Function Estimator Based on a Non‐parametric Transformation of the Data

Cites Work

• A note on limit theorems for perturbed empirical processes
• Relative efficiency and deficiency of kernel type estimators of smooth distribution functions
• Strong uniform consistency of integrals of density estimators
• Convergence rate of perturbed empirical distribution functions
• Some New Estimates for Distribution Functions
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