Deficiency of the sample quantile estimator with respect to kernel quantile estimators for censored data
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Publication:1906189
DOI10.1214/AOS/1176324625zbMath0847.62025OpenAlexW1979035036MaRDI QIDQ1906189
Publication date: 8 October 1996
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1214/aos/1176324625
Monte Carlo studydeficiencyrandomly right-censored datakernel quantile estimatorssample quantile estimatorequal covering probability
Asymptotic properties of parametric estimators (62F12) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05)
Related Items (20)
ON THE ASYMPTOTIC PROPERTIES FOR A NONPARAMETRIC CONDITIONAL QUANTILE ESTIMATOR IN PRESENCE OF RIGHT-CENSORING ⋮ A kernel nonparametric quantile estimator for right-censored competing risks data ⋮ Efficiency of estimators for quantile differences with left truncated and right censored data ⋮ Smooth estimate of quantiles under association ⋮ Empirical likelihood for conditional quantile with left-truncated and dependent data ⋮ Improved confidence intervals for quantiles ⋮ Asymptotic properties of conditional quantile estimator for censored dependent observations ⋮ \(\mathcal L_1\)-deficiency of the sample quantile estimator with respect to a kernel quantile estimator ⋮ CDF and survival function estimation with infinite-order kernels ⋮ Relative deficiency of quantile estimators for left truncated and right censored data ⋮ \(\mathcal L_1\)-deficiency of the Kaplan-Meier estimator. ⋮ Berry-Esseen bounds for the percentile residual life function estimators ⋮ Asymptotic Properties of Conditional Quantile Estimator Under Left-Truncated and α-Mixing Conditions ⋮ Strong uniform consistency of a nonparametric estimator of a conditional quantile for censored dependent data and functional regressors ⋮ A strong uniform convergence rate of kernel conditional quantile estimator under random censorship ⋮ Conditional quantile estimation with auxiliary information for left-truncated and dependent data ⋮ A New Family of Nonparametric Quantile Estimators ⋮ An exact bootstrap approach towards modification of the Harrell–Davis quantile function estimator for censored data ⋮ A distribution function estimator for the difference of order statistics from two independent samples ⋮ Edgeworth expansion for the kernel quantile estimator
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