Abstract
A bias‐corrected Akaike information criterion AICC is derived for self‐exciting threshold autoregressive (SETAR) models. The small sample properties of the Akaike information criteria (AIC, AICC) and the Bayesian information criterion (BIC) are studied using simulation experiments. It is suggested that AICC performs much better than AIC and BIC in small samples and should be put in routine usage. Copyright © 1998 Blackwell Publishers Ltd.
| Original language | English |
|---|---|
| Pages (from-to) | 113-124 |
| Journal | Journal of Time Series Analysis |
| Volume | 19 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Jan 1998 |
Citation
Wong, C. S., & Li, W. K. (1998). A note on the corrected Akaike information criterion for threshold autoregressive models. Journal of Time Series Analysis, 19(1), 113-124. doi: 10.1111/1467-9892.00080Keywords
- Corrected Akaike information criterion
- Kullback-Leibler information
- Threshold time series model