On the strong limiting behavior of local functionals of empirical processes based upon censored data

DOI10.1214/aop/1042644729zbMath0858.62037OpenAlexW2071867844MaRDI QIDQ1922091

John H. J. Einmahl, Paul Deheuvels

Publication date: 13 March 1997

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

Full work available at URL: https://doi.org/10.1214/aop/1042644729

zbMATH Keywords

empirical processesfunctional laws of the iterated logarithmkernel density estimatorlifetime distributionstrong lawsempirical measuresKaplan-Meier product-limit estimatorrandom censorship modelestimators of local functionals

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Applications of statistics to biology and medical sciences; meta analysis (62P10) Strong limit theorems (60F15) Functional limit theorems; invariance principles (60F17)

Related Items (6)

Functional limit laws for the increments of Kaplan-Meier product-limit processes and applications ⋮ Uniform-in-bandwidth kernel estimation for censored data ⋮ A law of the iterated logarithm for the empirical process based upon twice censored data ⋮ A strong consistency of a nonparametric estimate of entropy under random censorship ⋮ A strong representation of the product-limit estimator for left truncated and right censored data ⋮ Gaussian approximation to the extreme value index estimator of a heavy-tailed distribution under random censoring

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