Asymptotic uniform linearity of some robust statistics under exponentially subordinated strongly dependent models

DOI10.1016/S0167-7152(98)00300-9zbMath0939.62063OpenAlexW2004392139WikidataQ128100693 ScholiaQ128100693MaRDI QIDQ1962187

Kanchan Mukherjee, Shijie Chen

Publication date: 3 July 2000

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0167-7152(98)00300-9

zbMATH Keywords

regression quantilesL-estimatorsM-estimatorsweighted empirical processesR-estimators

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20) Linear regression; mixed models (62J05) Robustness and adaptive procedures (parametric inference) (62F35) Order statistics; empirical distribution functions (62G30)

Related Items (2)

ON M‐Estimation Under Long‐Range Dependence in Volatility ⋮ On location estimation for LARCH processes

Uses Software

• AS 229

Cites Work

• The behavior of robust estimators on dependent data
• Long- and short-range dependent sequences under exponential subordination
• Asymptotics of R-, MD- and LAD-estimators in linear regression models with long range dependent errors
• Regression quantiles and related processes under long range dependent errors
• L-Estimation for Linear Models
• M Estimators of Location for Gaussian and Related Processes With Slowly Decaying Serial Correlations
• Regression Quantiles
• Nonparametric Estimate of Regression Coefficients
• Robust Statistics
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