Please use this identifier to cite or link to this item:
Title: Threshold variable selection using nonparametric methods
Authors: Xia, Y. 
Li, W.-K.
Tong, H.
Keywords: Local linear smoother
Nonlinear time series
Single-index coefficient models
Threshold autoregressive (TAR) time series models
Issue Date: Jan-2007
Citation: Xia, Y.,Li, W.-K.,Tong, H. (2007-01). Threshold variable selection using nonparametric methods. Statistica Sinica 17 (1) : 265-287. ScholarBank@NUS Repository.
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.
Source Title: Statistica Sinica
ISSN: 10170405
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

checked on Jan 13, 2022

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.