Gauss-Newton and M-estimation for ARMA processes with infinite variance
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Publication:1272156
DOI10.1016/0304-4149(96)00063-4zbMath0902.62102OpenAlexW2013741185MaRDI QIDQ1272156
Publication date: 23 November 1998
Published in: Stochastic Processes and their Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/0304-4149(96)00063-4
Infinitely divisible distributions; stable distributions (60E07) Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)
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Cites Work
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- Spectral estimates and stable processes
- 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
- M-estimation for autoregression with infinite variance
- Time series: theory and methods.
- Functions of probability measures
- Parameter estimation for ARMA models with infinite variance innovations
- Recursive estimation of mixed autoregressive-moving average order
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