• 论文 •

STAR模型的滞后阶数选择与稳健性研究

• 出版日期:2014-06-15 发布日期:2014-07-14

Selection of the Lag Order of STAR Model and Its Robustness Analysis

Lingxiang Zhang

• Online:2014-06-15 Published:2014-07-14

Abstract: This paper discusses six information criteria of the applicability and robustness for determining the lag order of smooth transition autoregressive (STAR) models via Monte Carlo simulations. Simulation results show that in most situations, the error distribution of the data generation process does not influence the ability of the information criteria to correctly recognize the maximum lag order of a STAR model. For a short STAR model (a model with a lag order <5), the ACC criterion can determine the actual maximum lag order with higher accuracy, and exhibits robustness to different smooth transition coefficients and threshold values. The same results are generated by the Schwarz and ACC criteria for a long STAR model (lag order >5).