Asymptotics of self-weighted M-estimators for autoregressive models
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Publication:506578
DOI10.1007/S00184-016-0592-XzbMath1365.62349OpenAlexW2510198302MaRDI QIDQ506578
Publication date: 1 February 2017
Published in: Metrika (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s00184-016-0592-x
Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20)
Related Items (3)
Geometric ergodicity and conditional self‐weighted M‐estimator of a GRCAR(p) model with heavy‐tailed errors ⋮ Strong consistency for the conditional self-weighted \(M\) estimator of GRCA\((p)\) Models ⋮ Asymptotics for the conditional self-weighted M-estimator of GRCA(1) models with possibly heavy-tailed errors
Cites Work
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- Limit theory for moving averages of random variables with regularly varying tail probabilities
- Limit theory for the sample covariance and correlation functions of moving averages
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- Gauss-Newton and M-estimation for ARMA processes with infinite variance
- On convergence of LAD estimates in autoregression with infinite variance
- Self-weighted quasi-maximum exponential likelihood estimator for ARFIMA-GARCH models
- Weighted least absolute deviations estimation for ARFIMA time series with finite or infinite variance
- WEIGHTED LEAST ABSOLUTE DEVIATIONS ESTIMATION FOR ARMA MODELS WITH INFINITE VARIANCE
- Weighted quantile regression for AR model with infinite variance errors
- Regression and autoregression with infinite variance
- Autoregressive processes with infinite variance
- Least absolute deviation estimates in autoregression with infinite variance
- Self-Weighted Least Absolute Deviation Estimation for Infinite Variance Autoregressive Models
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