On kernel-based estimation of distribution function and its quantiles based on ranked set sampling
From MaRDI portal
Publication:6050712
DOI10.1080/00949655.2022.2153252MaRDI QIDQ6050712
Hani M. Samawi, Mehdi Amiri, Abbas Eftekharian
Publication date: 19 September 2023
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Cites Work
- Unnamed Item
- Normal probability plots and the estimation of distribution tails
- On estimating the distribution function and odds using ranked set sampling
- A Jonckheere-Terpstra-type test for perfect ranking in balanced ranked set sampling
- Estimating tails of probability distributions
- A note on the asymptotically optimal bandwidth for Nadaraya's quantile estimator
- Estimating densities, quantiles, quantile densities and density quantiles
- Ranked set sampling. Theory and applications
- On ranked-set sample quantiles and their applications
- Inferences on parametric estimation of distribution tails
- A bias reducing technique in kernel distribution function estimation
- Smooth estimators of distribution and density functions
- Variance Reduction Techniques for Estimating Value-at-Risk
- Quantile Estimation Using Ranked Set Samples from a Population with Known Mean
- On bias reduction in local linear smoothing
- Estimation of Tails and Related Quantities Using the Number of Near-Extremes
- Portfolio Value-at-Risk with Heavy-Tailed Risk Factors
- On kernel-based quantile estimation using different stratified sampling schemes with optimal allocation
- New distribution function estimators and tests of perfect ranking in concomitant-based ranked set sampling
- Estimating Quantile Sensitivities
- A Note on Quantiles in Large Samples
- Some New Estimates for Distribution Functions
This page was built for publication: On kernel-based estimation of distribution function and its quantiles based on ranked set sampling
