A CORRECTED AKAIKE INFORMATION CRITERION FOR VECTOR AUTOREGRESSIVE MODEL SELECTION

Journal of Time Series Analysis

Volumn 14, Issue 3, 1993, Pages 271-279

  Hurvich, Clifford M ^a   Tsai, Chih‐Ling ^a  

^a NEW YORK UNIVERSITY   (United States)

Author keywords

AIC; AICC; Kullback Leibler information

Indexed keywords

EID: 84981423152     PISSN: 01439782     EISSN: 14679892     Source Type: Journal    
DOI: 10.1111/j.1467-9892.1993.tb00144.x     Document Type: Article

References (15)

1. Fitting autoregressive models for prediction
2. Information theory and an extension of the maximum likelihood principle.
3. A new look at the statistical model identification
4. On the unbiasedness property of AIC for exact or approximating linear stochastic time series models
5. Regression and time series model selection in small samples
6. Comparison of criteria for estimating the order of a vector autoregressive process
7. The exact likelihood function of multivariate autoregressive‐moving average models
8. Estimating the dimension of a model
9. Asymptotically efficient selection of the order of the model for estimating paramters of a linear process