Abstract
Selecting the threshold variable is a key step in building a generalized threshold autoregressive (TAR) model. This paper proposes a semi-parametric method for this purpose that is based on a single-index functional coefficient model. The asymptotic distribution of the estimator is obtained. A simple algorithm is given and its convergence is proved. Some simulations are reported. Two data sets are analyzed, one of which gives strong statistical support for ratio-dependent predation in Ecology. Copyright © 2007 Institute of Statistical Science, Academia Sinica.
| Original language | English |
|---|---|
| Pages (from-to) | 265-287 |
| Journal | Statistica Sinica |
| Volume | 17 |
| Issue number | 1 |
| Publication status | Published - 2007 |
Citation
Xia, Y., Li, W.-K., & Tong, H. (2007). Threshold variable selection using nonparametric methods. Statistica Sinica, 17(1), 265-287.Keywords
- Local linear smoother
- Nonlinear time series
- Single-index coefficient models
- Threshold autoregressive (TAR) time series models