THE GLOBAL WEIGHTED LAD ESTIMATORS FOR FINITE/INFINITE VARIANCE ARMA(p,q) MODELS
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- Ke Zhu & Shiqing Ling, 2015.
"LADE-Based Inference for ARMA Models With Unspecified and Heavy-Tailed Heteroscedastic Noises,"
Journal of the American Statistical Association,
Taylor & Francis Journals, vol. 110(510), pages 784-794, June.
- Zhu, Ke & Ling, Shiqing, 2014. "LADE-based inference for ARMA models with unspecified and heavy-tailed heteroscedastic noises," MPRA Paper 59099, University Library of Munich, Germany.
- Ke Zhu, 2018. "Statistical inference for autoregressive models under heteroscedasticity of unknown form," Papers 1804.02348, arXiv.org.
- Zhu, Ke & Ling, Shiqing, 2013. "Global self-weighted and local quasi-maximum exponential likelihood estimators for ARMA-GARCH/IGARCH models," MPRA Paper 51509, University Library of Munich, Germany.
- Zhu, Ke & Li, Wai Keung, 2015.
"A bootstrapped spectral test for adequacy in weak ARMA models,"
Journal of Econometrics,
Elsevier, vol. 187(1), pages 113-130.
- Zhu, Ke & Li, Wai-Keung, 2013. "A bootstrapped spectral test for adequacy in weak ARMA models," MPRA Paper 51224, University Library of Munich, Germany.
- Yang, Yaxing & Ling, Shiqing, 2017. "Self-weighted LAD-based inference for heavy-tailed threshold autoregressive models," Journal of Econometrics, Elsevier, vol. 197(2), pages 368-381.
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