✦ LIBER ✦

Asymptotic properties of Kaplan-Meier estimator for censored dependent data

✍ Scribed by Zongwu Cai

Publisher: Elsevier Science
Year: 1998
Tongue: English
Weight: 337 KB
Volume: 37
Category: Article
ISSN: 0167-7152
DOI: 10.1016/s0167-7152(97)00141-7

No coin nor oath required. For personal study only.

✦ Synopsis

In some long term studies, a series of dependent and possibly censored failure times may be observed. Suppose that the failure times have a common marginal distribution function, and inferences about it are of interest to us. The main result of this paper is that, under certain regularity conditions, the Kaplan-Meier estimator can be expressed as the mean of random variables, with a remainder of some order. In addition, the asymptotic normality of the Kaplan-Meier estimator is derived. (~

📜 SIMILAR VOLUMES

On the asymptotic mean integrated square

On the asymptotic mean integrated squared error of a kernel density estimator for dependent data

✍ Jan Mielniczuk 📂 Article 📅 1997 🏛 Elsevier Science 🌐 English ⚖ 357 KB

Hall and Hart (1990) proved that the mean integrated squared error (MISE) of a marginal kernel density estimator from an infinite moving average process X1, )(2 .... may be decomposed into the sum of MISE of the same kernel estimator for a random sample of the same size and a term proportional to th

The asymptotics of maximum-likelihood es

The asymptotics of maximum-likelihood estimates of parameters based on a data type where the failure and the censoring time are dependent

✍ Di Chen; Jye-Chyi Lu 📂 Article 📅 1998 🏛 Elsevier Science 🌐 English ⚖ 654 KB

This article derives the asymptotic results of the maximum-likelihood estimates of the parameters in the general bivariate continuous distribution for the data type, in which the failure time and the censoring variables are dependent. This data type is motivated from life-testing two-component paral