The Kaplan–Meier estimator and hazard estimator for censored END survival time observations

Yongming Li; Yong Zhou

doi:10.1080/03610926.2019.1580737

The Kaplan–Meier estimator and hazard estimator for censored END survival time observations

Yongming Li^*
, Yong Zhou

^*Corresponding author for this work

School of Statistics

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

In this paper, the survival function and hazard rate estimator by the Kaplan–Meier method are considered, where the survival times and censoring times are two sequences of extended negatively dependent. Under some suitable conditions, the uniform strong approximation rates for the survival function and hazard rate estimator are established with the rate O(n^-1/2 log^1/2n) a.s., also, their strong representations are obtained with a remainder O(n^-1/2 log^1/2n) a.s. Our results generalize and extend the corresponding ones in the related literatures.

Original language	English
Pages (from-to)	2690-2702
Number of pages	13
Journal	Communications in Statistics - Theory and Methods
Volume	49
Issue number	11
DOIs	https://doi.org/10.1080/03610926.2019.1580737
State	Published - 2 Jun 2020

Keywords

62G05
62G20
Extended negatively dependent
Kaplan–Meier method
hazard rate
strong approximation
strong representation
survival function

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10.1080/03610926.2019.1580737

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title = "The Kaplan–Meier estimator and hazard estimator for censored END survival time observations",

abstract = "In this paper, the survival function and hazard rate estimator by the Kaplan–Meier method are considered, where the survival times and censoring times are two sequences of extended negatively dependent. Under some suitable conditions, the uniform strong approximation rates for the survival function and hazard rate estimator are established with the rate O(n-1/2 log1/2n) a.s., also, their strong representations are obtained with a remainder O(n-1/2 log1/2n) a.s. Our results generalize and extend the corresponding ones in the related literatures.",

keywords = "62G05, 62G20, Extended negatively dependent, Kaplan–Meier method, hazard rate, strong approximation, strong representation, survival function",

author = "Yongming Li and Yong Zhou",

note = "Publisher Copyright: {\textcopyright} 2019, {\textcopyright} 2019 Taylor \& Francis Group, LLC.",

year = "2020",

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TY - JOUR

T1 - The Kaplan–Meier estimator and hazard estimator for censored END survival time observations

AU - Li, Yongming

AU - Zhou, Yong

PY - 2020/6/2

Y1 - 2020/6/2

N2 - In this paper, the survival function and hazard rate estimator by the Kaplan–Meier method are considered, where the survival times and censoring times are two sequences of extended negatively dependent. Under some suitable conditions, the uniform strong approximation rates for the survival function and hazard rate estimator are established with the rate O(n-1/2 log1/2n) a.s., also, their strong representations are obtained with a remainder O(n-1/2 log1/2n) a.s. Our results generalize and extend the corresponding ones in the related literatures.

AB - In this paper, the survival function and hazard rate estimator by the Kaplan–Meier method are considered, where the survival times and censoring times are two sequences of extended negatively dependent. Under some suitable conditions, the uniform strong approximation rates for the survival function and hazard rate estimator are established with the rate O(n-1/2 log1/2n) a.s., also, their strong representations are obtained with a remainder O(n-1/2 log1/2n) a.s. Our results generalize and extend the corresponding ones in the related literatures.

KW - 62G05

KW - 62G20

KW - Extended negatively dependent

KW - Kaplan–Meier method

KW - hazard rate

KW - strong approximation

KW - strong representation

KW - survival function

UR - https://www.scopus.com/pages/publications/85063915309

U2 - 10.1080/03610926.2019.1580737

DO - 10.1080/03610926.2019.1580737

M3 - 文章

AN - SCOPUS:85063915309

SN - 0361-0926

VL - 49

SP - 2690

EP - 2702

JO - Communications in Statistics - Theory and Methods

JF - Communications in Statistics - Theory and Methods

IS - 11

ER -

The Kaplan–Meier estimator and hazard estimator for censored END survival time observations

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Keywords

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