Title of article
A new method for proving weak convergence results applied to nonparametric estimators in survival analysis
Author/Authors
Dauxois، نويسنده , , Jean-Yves، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2000
Pages
8
From page
327
To page
334
Abstract
Using the limit theorem for stochastic integral obtained by Jakubowski et al. (Probab. Theory Related Fields 81 (1989) 111–137), we introduce in this paper a new method for proving weak convergence results of empirical processes by a martingale method which allows discontinuities for the underlying distribution. This is applied to Nelson–Aalen and Kaplan–Meier processes. We also prove that the same conclusion can be drawn for Hjortʹs nonparametric Bayes estimators of the cumulative distribution function and cumulative hazard rate.
Keywords
Stochastic integral , Counting process , Censored data , weak convergence , Product integral , Gaussian process , Martingale
Journal title
Stochastic Processes and their Applications
Serial Year
2000
Journal title
Stochastic Processes and their Applications
Record number
1576734
Link To Document