Gauss-Newton and M-estimation for ARMA processes with infinite variance
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References listed on IDEAS
- Davis, Richard A. & Knight, Keith & Liu, Jian, 1992. "M-estimation for autoregressions with infinite variance," Stochastic Processes and their Applications, Elsevier, vol. 40(1), pages 145-180, February.
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- Rongning Wu, 2013. "M-estimation for general ARMA Processes with Infinite Variance," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(3), pages 571-591, September.
- Rongning Wu & Richard A. Davis, 2010. "Least absolute deviation estimation for general autoregressive moving average time-series models," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(2), pages 98-112, March.
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"Aggregation of exponential smoothing processes with an application to portfolio risk evaluation,"
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"LADE-Based Inference for ARMA Models With Unspecified and Heavy-Tailed Heteroscedastic Noises,"
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- Xinghui Wang & Shuhe Hu, 2017. "Asymptotics of self-weighted M-estimators for autoregressive models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(1), pages 83-92, January.
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More about this item
KeywordsGauss-Newton estimate Heavy-tails Stable distributions M-estimation ARMA processes;
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