Model selection for infinite variance time series
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Publication:4843863
DOI10.1080/03610929508831529zbMath0825.62314OpenAlexW2087188527MaRDI QIDQ4843863
Publication date: 17 August 1995
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610929508831529
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Cites Work
- Local asymptotic admissibility of a generalization of Akaike's model selection rule
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- On predictive least squares principles
- Semi-parametric estimation of a stationary, non-necessary causal AR(P) process with infinite variance
- A Predictive Least-Squares Principle
- SELECTING ORDER FOR GENERAL AUTOREGRESSIVE MODELS BY MINIMUM DESCRIPTION LENGTH
- A derivation of the information criteria for selecting autoregressive models
- Model-structure selection by cross-validation
- Order selection for AR models by predictive least squares
- Regression and time series model selection in small samples
- A Method for Simulating Stable Random Variables
- Minimum error dispersion linear filtering of scalar symmetric stable processes
- A Bayesian extension of the minimum AIC procedure of autoregressive model fitting
- The consistency of the L1norm estimates in arma models
- "Infinite Variance" and Research Strategy in Time Series Analysis
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