Quantile Estimation in the Presence of Auxiliary Information under Negatively Associated Samples
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Publication:2892631
DOI10.1080/03610926.2010.508865zbMath1239.62030OpenAlexW2013903036MaRDI QIDQ2892631
Publication date: 19 June 2012
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610926.2010.508865
Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05)
Cites Work
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- Empirical likelihood ratio confidence regions
- Some concepts of negative dependence
- A note on the almost sure convergence of sums of negatively dependent random variables
- Smoothed empirical likelihood confidence intervals for quantiles
- \(M\)-estimation and quantile estimation in the presence of auxiliary information
- Moment inequalities and weak convergence for negatively associated sequences
- Smooth estimate of quantiles under association
- Uniformly asymptotic normality of the regression weighted estimator for negatively associated samples.
- Asymptotic normality of the kernel estimate of a probability density function under association
- Some maximal inequalities and complete convergences of negatively associated random sequences
- The characterization of equilibrium potentials and last exit distributions for elliptic diffusion processes
- Complete convergence for weighted sums of NA sequences
- Negative association of random variables, with applications
- Empirical likelihood ratio confidence intervals for a single functional
- Berry-esseen bounds for smooth estimator of a distribution function under association
- Empirical likelihood estimation for finite populations and the effective usage of auxiliary information
- The weak convergence for functions of negatively associated random variables
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