Translator Disclaimer
August 1997 Smoothed Cox regression
Dorota M. Dabrowska
Ann. Statist. 25(4): 1510-1540 (August 1997). DOI: 10.1214/aos/1031594730

Abstract

Nonparametric regression was shown by Beran and McKeague and Utikal to provide a flexible method for analysis of censored failure times and more general counting processes models in the presence of covariates. We discuss application of kernel smoothing towards estimation in a generalized Cox regression model with baseline intensity dependent on a covariate. Under regularity conditions we show that estimates of the regression parameters are asymptotically normal at rate root-n, and we also discuss estimation of the baseline cumulative hazard function and related parameters.

Citation

Download Citation

Dorota M. Dabrowska. "Smoothed Cox regression." Ann. Statist. 25 (4) 1510 - 1540, August 1997. https://doi.org/10.1214/aos/1031594730

Information

Published: August 1997
First available in Project Euclid: 9 September 2002

zbMATH: 0936.62046
MathSciNet: MR1463563
Digital Object Identifier: 10.1214/aos/1031594730

Subjects:
Primary: 62G05, 62M09

Rights: Copyright © 1997 Institute of Mathematical Statistics

JOURNAL ARTICLE
31 PAGES


SHARE
Vol.25 • No. 4 • August 1997
Back to Top