A new proof of strong consistency of kernel estimation of density function and mode under random censorship.

DOI10.1016/S0167-7152(02)00166-9zbMath1050.62054MaRDI QIDQ1871257

Ali Gannoun, Jérôme Saracco

Publication date: 7 May 2003

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

zbMATH Keywords

Censored dataKernel density estimationStrong consistencyKaplan-- Meier estimatorMode estimation

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Censored data models (62N01) Estimation in survival analysis and censored data (62N02)

Related Items (2)

Asymptotic properties of the kernel mode estimator under twice censorship model ⋮ Consistent estimation of the density and hazard rate functions for censored data via the wavelet method

Cites Work

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• On the asymptotic normality of the kernel estimators of the density function and its derivatives under censoring
• Some inequalities for the kernel density estimator under random censorship^∗
• On Non-Parametric Estimates of Density Functions and Regression Curves
• On Strong Consistency of Density Estimates
• On Estimation of a Probability Density Function and Mode

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