Regularization and variable selection for infinite variance autoregressive models
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Publication:447619
DOI10.1016/j.jspi.2012.03.014zbMath1253.62065OpenAlexW2103244880MaRDI QIDQ447619
Yanbiao Xiang, Ganggang Xu, Suojin Wang, Zheng Yan Lin
Publication date: 4 September 2012
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.2012.03.014
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- The Adaptive Lasso and Its Oracle Properties
- One-step sparse estimates in nonconcave penalized likelihood models
- Wold decomposition, prediction and parameterization of stationary processes with infinite variance
- Consistency of Araike's information criterion for infinite variance autoregressive processes
- M-estimation for autoregression with infinite variance
- A simple general approach to inference about the tail of a distribution
- Estimating the dimension of a model
- Heavy tail modeling and teletraffic data. (With discussions and rejoinder)
- Asymptotics for Lasso-type estimators.
- On the asymptotics of constrained \(M\)-estimation
- COBS: qualitatively constrained smoothing via linear programming
- Dealing with the multiplicity of solutions of the \(\ell _{1}\) and \(\ell _{\infty }\) regression models
- Quantile smoothing splines
- Regression coefficient and autoregressive order shrinkage and selection via the lasso
- Self-Weighted Least Absolute Deviation Estimation for Infinite Variance Autoregressive Models
- "Infinite Variance" and Research Strategy in Time Series Analysis
- Regularity and minimality of infinite variance processes
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