Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/105433
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
URI: http://scholarbank.nus.edu.sg/handle/10635/105433
ISSN: 10170405
Appears in Collections:Staff Publications

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