کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1146879 957534 2009 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Asymptotics for non-parametric likelihood estimation with doubly censored multivariate failure times
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات آنالیز عددی
پیش نمایش صفحه اول مقاله
Asymptotics for non-parametric likelihood estimation with doubly censored multivariate failure times
چکیده انگلیسی

This paper considers non-parametric estimation of a multivariate failure time distribution function when only doubly censored data are available, which occurs in many situations such as epidemiological studies. In these situations, each of multivariate failure times of interest is defined as the elapsed time between an initial event and a subsequent event and the observations on both events can suffer censoring. As a consequence, the estimation of multivariate distribution is much more complicated than that for multivariate right- or interval-censored failure time data both theoretically and practically. For the problem, although several procedures have been proposed, they are only ad-hoc approaches as the asymptotic properties of the resulting estimates are basically unknown. We investigate both the consistency and the convergence rate of a commonly used non-parametric estimate and show that as the dimension of multivariate failure time increases or the number of censoring intervals of multivariate failure time decreases, the convergence rate for non-parametric estimate decreases, and is slower than that with multivariate singly right-censored or interval-censored data.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Multivariate Analysis - Volume 100, Issue 8, September 2009, Pages 1802–1815
نویسندگان
, ,