Asymptotic properties for M-estimators in linear models with dependent random errors
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Publication:2437863
DOI10.1016/j.jspi.2013.12.005zbMath1432.62206OpenAlexW2069497630MaRDI QIDQ2437863
Jun Fan, Ailing Yan, Nai-Hua Xiu
Publication date: 13 March 2014
Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jspi.2013.12.005
linear modellaw of the iterated logarithmM-estimatorsmoderate deviationsstrong Bahadur representation
Asymptotic properties of parametric estimators (62F12) Linear regression; mixed models (62J05) Large deviations (60F10)
Related Items
Bahadur representations of M-estimators and their applications in general linear models, Asymptotics of M‐estimator in multivariate linear regression models for a class of random errors, Asymptotic properties of M estimators in classical linear models with φ -mixing random errors, An exponential inequality and its application to \(M\) estimators in multiple linear models, Asymptotic property of \(M\) estimator in classical linear models under dependent random errors, On the Strong Consistency of M-Estimates in Linear Models for Negatively Superadditive Dependent Errors
Cites Work
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- Delta method in large deviations and moderate deviations for estimators
- Large deviations for \(M\)-estimators
- \(M\)-estimation of linear models with dependent errors
- On moderate deviation theory in estimation
- Large deviations of estimators
- Moderate and Cramér-type large deviation theorems for M-estimators
- Large sample point estimation: A large deviation theory approach
- M-estimators in linear models with long range dependent errors
- Behavior of robust estimators in the regression model with dependent errors
- Estimates of location: a large deviation comparison
- Asymptotics of R-, MD- and LAD-estimators in linear regression models with long range dependent errors
- A general Bahadur representation of \(M\)-estimators and its application to linear regression with nonstochastic designs
- Moderate deviations for M-estimators in linear models with \(\phi\)-mixing errors
- A general class of exponential inequalities for martingales and ratios
- Moderate deviations for \(M\)-estimators
- On Bernstein-type inequalities for martingales.
- M-estimation for linear models with spatially-correlated errors
- Linear representation of M-estimates in linear models
- Large deviations of semimartingales via convergence of the predictable characteristics
- Rates of Convergence of Estimates and Test Statistics
- A Measure of Asymptotic Efficiency for Tests of a Hypothesis Based on the sum of Observations
- Strong consistency of M-estimates in linear models
