Translator Disclaimer
June, 1983 Smoothing Counting Process Intensities by Means of Kernel Functions
Henrik Ramlau-Hansen
Ann. Statist. 11(2): 453-466 (June, 1983). DOI: 10.1214/aos/1176346152

Abstract

The kernel function method developed during the last twenty-five years to estimate a probability density function essentially is a way of smoothing the empirical distribution function. This paper shows how one can generalize this method to estimate counting process intensities using kernel functions to smooth the nonparametric Nelson estimator for the cumulative intensity. The properties of the estimator for the intensity itself are investigated, and uniform consistency and asymptotic normality are proved. We also give an illustrative numerical example.

Citation

Download Citation

Henrik Ramlau-Hansen. "Smoothing Counting Process Intensities by Means of Kernel Functions." Ann. Statist. 11 (2) 453 - 466, June, 1983. https://doi.org/10.1214/aos/1176346152

Information

Published: June, 1983
First available in Project Euclid: 12 April 2007

zbMATH: 0514.62050
MathSciNet: MR696058
Digital Object Identifier: 10.1214/aos/1176346152

Subjects:
Primary: 60G55
Secondary: 62G05, 62P05

Rights: Copyright © 1983 Institute of Mathematical Statistics

JOURNAL ARTICLE
14 PAGES


SHARE
Vol.11 • No. 2 • June, 1983
Back to Top