Asymptotically efficient order selection in nonstationary AR processes
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Publication:5936978
DOI10.1007/BF02595741zbMath0971.62048MaRDI QIDQ5936978
Publication date: 23 August 2001
Published in: Test (Search for Journal in Brave)
consistencyasymptotic efficiencyautoregressive processesdiscrete time seriesmodel selection criterianonstationary processes
Asymptotic properties of parametric estimators (62F12) Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20)
Cites Work
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- Order selection in nonstationary autoregressive models
- Consistency properties of least squares estimates of autoregressive parameters in ARMA models
- Asymptotically efficient selection of the order by the criterion autoregressive transfer function
- Asymptotically efficient selection of the order of the model for estimating parameters of a linear process
- On predictive least squares principles
- Estimating the dimension of a model
- Asymptotically efficient autoregressive model selection for multistep prediction
- Testing cointegration in infinite order vector autoregressive processes
- Model selection under nonstationarity: Autoregressive models and stochastic linear regression models
- Fitting autoregressive models for prediction
- Distribution of the Estimators for Autoregressive Time Series With a Unit Root
- The Order of Differencing in ARIMA Models
- Regression and time series model selection in small samples
- Selection of the order of an autoregressive model by Akaike's information criterion
- Asymptotic efficiency of model selection criteria: the nonzero mean gaussian ar(∞) case
