Adaptive choice of trimming proportion in trimmed least-squares estimation.
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Publication:1380584
DOI10.1016/S0167-7152(96)00145-9zbMath1064.62540OpenAlexW2095004282MaRDI QIDQ1380584
Publication date: 1997
Published in: Statistics \& Probability Letters (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/s0167-7152(96)00145-9
Linear regression; mixed models (62J05) Robustness and adaptive procedures (parametric inference) (62F35)
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- Large sample properties of Jaeckel's adaptive trimmed mean
- Regression rank scores and regression quantiles
- Adaptive choice of trimming proportions
- Tests of linear hypotheses based on regression rank scores
- Asymptotic normality ofr-estimates in the linear model
- Mallows-Type Bounded-Influence-Regression Trimmed Means
- Trimmed Least Squares Estimation in the Linear Model
- Asymptotic Behavior of the Number of Regression Quantile Breakpoints
- An effective method for computing regression quantiles
- Adaptive Robust Procedures: A Partial Review and Some Suggestions for Future Applications and Theory
- Regression Quantiles
- Selection of Trimming Proportions for Robust Adaptive Trimmed Means
- Estimating Regression Coefficients by Minimizing the Dispersion of the Residuals
- Robust Estimation of a Location Parameter
- Asymptotic Linearity of a Rank Statistic in Regression Parameter
- Nonparametric Estimate of Regression Coefficients
- More Light on the Kurtosis and Related Statistics
- An Adaptive Procedure for Selecting the Population with Largest Location Parameter
- Robust Statistics
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