On the penalty factor for autoregressive order selection in finite samples

被引:27
|
作者
Broersen, PMT
Wensink, HE
机构
[1] Department of Applied Physics, Delft University of Technology, Delft
关键词
D O I
10.1109/78.489055
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The order selection criterion that selects models with the smallest squared error of prediction is the best. The finite sample theory describes equivalents for asymptotic order selection criteria that are better in the finite sample practice. This correction for finite sample statistics is the most important. Afterwards, a preference in order selection criteria can be obtained by computing an optimal value for the penalty factor based on a subjective balance of the risks of overfitting and underfitting.
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页码:748 / 752
页数:5
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