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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/41259

Title: Efficient estimation in smooth threshold autoregressive (1) models
Author/Creator: Nur, D.; Nair, G. M.; Yatawara, N. D.
Institution: The University of Newcastle. Faculty of Science & Information Technology, School of Mathematical and Physical Sciences
Description: Verifiable conditions are given for the existence of efficient estimation in Smooth Threshold Autoregressive models of order 1. The paper establishes local asymptotic normality in the semi-parametric setting which is then used to discuss adaptive and efficient estimates of the models. It is found that the adaptation is satisfied if the error densities are symmetric. Simulation results are presented to compare the conditional least squares estimate with the adaptive and efficient estimates for the models.
Relation: Journal of Statistical Theory and Practice Vol. 2, Issue 1, p. 83-94
Relation: http://journalstp.gracescientific.com/Volume2Number1.aspx
Date: 2008
Publisher: Grace Scientific Publishing
Keyword(s): adaptive estimation; efficient estimation; locally asymptotically normal; non-linear time series; smooth threshold autoregressive; stationarity
Resource Type: journal article
Identifier: http://hdl.handle.net/1959.13/41259
Identifier: ISSN:1559-8608

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