Bahadur representation of the kernel quantile estimator under random censorship

DOI10.1006/JMVA.1995.1052zbMath0898.62059OpenAlexW2078760954MaRDI QIDQ1898403

Xiaojing Xiang

Publication date: 17 September 1995

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1006/jmva.1995.1052

zbMATH Keywords

Bahadur representationlaw of the iterated logarithmKaplan-Meier estimatorrandom censorshipkernel quantile estimator

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Strong limit theorems (60F15)

Related Items (5)

A kernel nonparametric quantile estimator for right-censored competing risks data ⋮ Bahadur representation of linear kernel quantile estimator of VaR under \(\alpha \)-mixing assumptions ⋮ The Bahadur representation for kernel-type estimator of the quantile function under strong mixing and censored data ⋮ A note on the Bahadur representation of sample quantiles for \(\alpha \)-mixing random variables ⋮ Bahadur representation of the kernel quantile estimator under truncated and censored data.

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