The Annals of Statistics

A Note on Data-Adaptive Kernel Estimation of the Hazard and Density Function in the Random Censorship Situation

Helmut Schafer

Full-text: Open access

Abstract

In a recent paper, Tanner (1983) proves pointwise consistency of a variable bandwidth kernel estimator for the hazard function. In the present note, a simplified proof of uniform consistency of a data-adaptive kernel estimator with certain additional advantages is given.

Article information

Source
Ann. Statist., Volume 13, Number 2 (1985), 818-820.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176349560

Digital Object Identifier
doi:10.1214/aos/1176349560

Mathematical Reviews number (MathSciNet)
MR790578

Zentralblatt MATH identifier
0606.62040

JSTOR
links.jstor.org

Subjects
Primary: 62P10: Applications to biology and medical sciences
Secondary: 62G05: Estimation 65D10: Smoothing, curve fitting

Keywords
Nonparametric estimation density function hazard function kernel estimators sample-point-dependent bandwidths random censorship model

Citation

Schafer, Helmut. A Note on Data-Adaptive Kernel Estimation of the Hazard and Density Function in the Random Censorship Situation. Ann. Statist. 13 (1985), no. 2, 818--820. doi:10.1214/aos/1176349560. https://projecteuclid.org/euclid.aos/1176349560


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