Random weighted bootstrap method for recurrent events with informative censoring

DOI10.1007/s10985-005-5236-9zbMath1120.62097OpenAlexW2049920583WikidataQ51958850 ScholiaQ51958850MaRDI QIDQ995967

Chin-Tsang Chiang, Lancelot F. James, Mei-Cheng Wang

Publication date: 10 September 2007

Published in: Lifetime Data Analysis (Search for Journal in Brave)

Full work available at URL: http://ntur.lib.ntu.edu.tw/bitstream/246246/181485/1/04.pdf

zbMATH Keywords

asymptotic normalityweighted bootstrapbandwidthcross-validationconfidence intervalPoisson processkernel estimatorwild bootstrapnaive bootstrapindependent censoringlongitudinal studyoccurrence rate function

Mathematics Subject Classification ID

Density estimation (62G07) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric statistical resampling methods (62G09) Estimation in survival analysis and censored data (62N02)

Related Items (7)

Three-step risk inference in insurance ratemaking ⋮ Applications of the Fractional-Random-Weight Bootstrap ⋮ Cramér's type results for some bootstrapped \(U\)-statistics ⋮ On the performance of weighted bootstrapped kernel deconvolution density estimators ⋮ Confidence intervals for median survival time with recurrent event data ⋮ On a multidimensional general bootstrap for empirical estimator of continuous-time semi-Markov kernels with applications ⋮ Two-step risk analysis in insurance ratemaking

Cites Work

• On a second-order asymptotic property of the Bayesian bootstrap mean
• On the asymptotic accuracy of Efron's bootstrap
• A rank statistics approach to the consistency of a general bootstrap
• Bootstrap methods: another look at the jackknife
• Exchangeably weighted bootstraps of the general empirical process
• A Bayesian method for weighted sampling
• A study of a class of weighted bootstrap for censored data
• A large sample study of the Bayesian bootstrap
• Smoothing estimation of rate function for recurrent event data with informative censoring
• Analyzing Recurrent Event Data With Informative Censoring
• Adaptive Bandwidth Choice for Kernel Regression

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