On the convergence rates of kernel estimator and hazard estimator for widely dependent samples
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Publication:824505
DOI10.1186/S13660-018-1659-1zbMath1497.62083OpenAlexW2805506946WikidataQ55018455 ScholiaQ55018455MaRDI QIDQ824505
Chao Liu, Yongming Li, Yong Zhou
Publication date: 15 December 2021
Published in: Journal of Inequalities and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1186/s13660-018-1659-1
Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05)
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Complete \(f\)-moment convergence for maximal randomly weighted sums of arrays of rowwise widely orthant dependent random variables and its statistical applications ⋮ The asymptotic properties for the estimators of the survival function and failure rate function based on WOD samples
Cites Work
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- Kernel density and hazard rate estimation for censored dependent data
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- Uniform asymptotics for the finite-time ruin probability of a dependent risk model with a constant interest rate
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- Complete consistency for the estimator of nonparametric regression models based on extended negatively dependent errors
- On the rate of strong convergence for a recursive probability density estimator of END samples and its applications
- Nonlinear wavelet density and hazard rate estimation for censored data under dependent observations
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