Asymptotic expansion for ISE of kernel density estimators under censored dependent model

DOI10.1016/j.spl.2009.05.003zbMath1169.62025OpenAlexW2093375902MaRDI QIDQ840797

Sarah Jomhoori, Vahid Fakoor, Hasanali Azarnoosh

Publication date: 14 September 2009

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2009.05.003

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic distribution theory in statistics (62E20) Censored data models (62N01)

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Some Asymptotic Results of Kernel Density Estimators Under Random Left-Truncation and Dependent Data

Cites Work

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• Central limit theorem for integrated square error of multivariate nonparametric density estimators
• Large sample behaviour of the product-limit estimator on the whole line
• A correction to and improvement of: ``Strong approximations of some biometric estimates under random censorship
• Limit theorems for stochastic measures of the accuracy of density estimators
• A central limit theorem for the integrated square error of the kernel density estimators with randomly censored data
• Asymptotic properties of Kaplan-Meier estimator for censored dependent data
• A note on the integrated square errors of kernel density estimators under random censorship
• On some global measures of the deviations of density function estimates
• Nonparametric Estimation and Identification of Nonlinear ARCH Time Series Strong Convergence and Asymptotic Normality: Strong Convergence and Asymptotic Normality
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• An almost sure invariance principle for the empirical distribution function of mixing random variables
• Tail behaviour of the stationary density of general non-linear autoregressive processes of order 1