Threshold variable selection using nonparametric methods

Yingcun XIA, Wai Keung LI, Howell TONG

Research output: Contribution to journalArticles

7 Citations (Scopus)

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 languageEnglish
Pages (from-to)265-287
JournalStatistica Sinica
Volume17
Issue number1
Publication statusPublished - 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

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