Abstract
In this paper, we study a new model called the smooth buffered autoregressive (SBA) model. A sufficient condition is given for geometric ergodicity. A conditional least squares (CLS) estimation procedure is discussed, and consistency and normality of the estimators are derived. We investigate the effectiveness of our methods by simulation studies. Two applications are considered: annual sunspot number and the U.S. unemployment rate. Copyright © 2019 Elsevier B.V. All rights reserved.
| Original language | English |
|---|---|
| Pages (from-to) | 196-210 |
| Journal | Journal of Statistical Planning and Inference |
| Volume | 206 |
| Early online date | Oct 2019 |
| DOIs | |
| Publication status | Published - May 2020 |
Citation
Lu, R., & Yu, P. L. H. (2020). Smooth buffered autoregressive time series models. Journal of Statistical Planning and Inference, 206, 196-210. doi: 10.1016/j.jspi.2019.09.012Keywords
- Conditional least squares
- Geometric ergodicity
- Threshold model
