\(L_{1}\) regression estimate and its bootstrap
From MaRDI portal
Publication:1042963
DOI10.1007/S11425-009-0087-6zbMath1176.62009OpenAlexW1978149294MaRDI QIDQ1042963
Publication date: 7 December 2009
Published in: Science in China. Series A (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11425-009-0087-6
Nonparametric regression and quantile regression (62G08) Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Linear regression; mixed models (62J05) Nonparametric estimation (62G05) Central limit and other weak theorems (60F05) Nonparametric statistical resampling methods (62G09)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Bootstrapping sample quantiles in non-regular cases
- Asymptotic normality of minimum \(L_ 1\)-norm estimates in linear models
- On the asymptotic properties of the jackknife histogram
- Bootstrap of the mean in the infinite variance case
- Efficiency and robustness in resampling
- Some results on the influence of extremes on the bootstrap
- On the bootstrap of the sample mean in the infinite variance case
- Exchangeably weighted bootstraps of the general empirical process
- Confidence intervals for endpoints of a c.d.f. via bootstrap
- Generalized bootstrap for estimators of minimizers of convex functions
- Generalised bootstrap in non-regular M-estimation problems
- Limiting distributions for \(L_1\) regression estimators under general conditions
- Asymptotic Theory of Least Absolute Error Regression
- The estimating function bootstrap
- Asymptotics for L1‐estimators of regression parameters under heteroscedasticityY
This page was built for publication: \(L_{1}\) regression estimate and its bootstrap