Strong representation results of the Kaplan-Meier estimator for censored negatively associated data

DOI10.1186/1029-242X-2013-340zbMath1282.62084OpenAlexW2165895437WikidataQ59301100 ScholiaQ59301100MaRDI QIDQ2437679

Qunying Wu, Ping Yan Chen

Publication date: 13 March 2014

Published in: Journal of Inequalities and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1186/1029-242x-2013-340

zbMATH Keywords

Kaplan-Meier estimatorstrong convergence ratesrandom censorship modelNA sequencesstrong representations

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Censored data models (62N01) Estimation in survival analysis and censored data (62N02)

Related Items (4)

Strong representations of the Kaplan-Meier estimator and hazard estimator with censored widely orthant dependent data ⋮ The Kaplan–Meier estimator and hazard estimator for censored END survival time observations ⋮ SOME LIMITING BEHAVIOR FOR ASYMPTOTICALLY NEGATIVE ASSOCIATED RANDOM VARIABLES ⋮ Almost sure central limit theorem for self-normalized partial sums of negatively associated random variables

Cites Work

• Chover's law of the iterated logarithm for negatively associated sequences
• Functional laws of the iterated logarithm for the product-limit estimator of a distribution function under random censorship or truncation
• A Berry-Esseen type bound in kernel density estimation for strong mixing censored samples
• A note on the almost sure convergence of sums of negatively dependent random variables
• The Kaplan-Meier estimate for dependent failure time observations
• Convergence of the conditional Kaplan-Meier estimate under strong mixing
• Negative association of random variables, with applications
• A large sample study of the life table and product limit estimates under random censorship
• A law of the iterated logarithm of partial sums for NA random variables
• A LIL type result for the product limit estimator
• Modification of the Greenwood Formula for Correlated Response Times
• Estimating a distribution function for censored time series data

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