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September, 1989 Model Selection Under Nonstationarity: Autoregressive Models and Stochastic Linear Regression Models
B. M. Potscher
Ann. Statist. 17(3): 1257-1274 (September, 1989). DOI: 10.1214/aos/1176347267

Abstract

We give sufficient conditions for strong consistency of estimators for the order of general nonstationary autoregressive models based on the minimization of an information criterion a la Akaike's (1969) AIC. The case of a time-dependent error variance is also covered by the analysis. Furthermore, the more general case of regressor selection in stochastic regression models is treated.

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B. M. Potscher. "Model Selection Under Nonstationarity: Autoregressive Models and Stochastic Linear Regression Models." Ann. Statist. 17 (3) 1257 - 1274, September, 1989. https://doi.org/10.1214/aos/1176347267

Information

Published: September, 1989
First available in Project Euclid: 12 April 2007

zbMATH: 0683.62049
MathSciNet: MR1015149
Digital Object Identifier: 10.1214/aos/1176347267

Subjects:
Primary: 62M10
Secondary: 60G10, 62F12, 62J05, 93E12

Rights: Copyright © 1989 Institute of Mathematical Statistics

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Vol.17 • No. 3 • September, 1989
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