A law of the iterated logarithm for error density estimator in censored linear regression

DOI10.1080/10485252.2022.2042814OpenAlexW4212932560MaRDI QIDQ5078821

Fuxia Cheng

Publication date: 25 May 2022

Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10485252.2022.2042814

zbMATH Keywords

bandwidthKaplan-Meier estimatorkernel density estimationright censored dataLIL

Mathematics Subject Classification ID

Censored data models (62N01) Estimation in survival analysis and censored data (62N02) Nonparametric inference (62Gxx)

Cites Work

• Maximum deviation of error density estimators in censored linear regression
• The tight constant in the Dvoretzky-Kiefer-Wolfowitz inequality
• Estimating regression parameters using linear rank tests for censored data
• Asymptotic behavior of the empiric distribution of M-estimated residuals from a regression model with many parameters
• Kernel density and hazard function estimation in the presence of censoring
• Large sample theory of a modified Buckley-James estimator for regression analysis with censored data
• Weighted empirical processes in dynamic nonlinear models.
• A missing information principle and \(M\)-estimators in regression analysis with censored and truncated data
• Residuals density estimation in censored linear regression model
• Empirical process of residuals for high-dimensional linear models
• Asymptotic Minimax Character of the Sample Distribution Function and of the Classical Multinomial Estimator
• Linear regression with censored data
• Laws of the iterated logarithm for nonparametric density estimators
• The strong uniform consistency of kernel estimator of a smooth distribution function in censored linear regression

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