Generalised likelihood ratio tests for spectral density

Fan, J.Q. and Zhang, W.Y. (2004) Generalised likelihood ratio tests for spectral density. Biometrika, 91 (1). pp. 195-209. ISSN 0006-3444. (The full text of this publication is not available from this repository)

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Official URL
http://dx.doi.org/10.1093/biomet/91.1.195

Abstract

There are few techniques available for testing whether or not a family of parametric times series models fits a set of data reasonably well without serious restrictions on the forms of alternative models. In this paper, we consider generalised likelihood ratio tests of whether or not the spectral density function of a stationary time series admits certain parametric forms. We propose a bias correction method for the generalised likelihood ratio test of Fan et al. (2001). In particular, our methods can be applied to test whether or not a residual series is white noise. Sampling properties of the proposed tests are established. A bootstrap approach is proposed for estimating the null distribution of the test statistics. Simulation studies investigate the accuracy of the proposed bootstrap estimate and compare the power of the various ways of constructing the generalised likelihood ratio tests as well as some classic methods like the Cramer-von Mises and Ljung-Box tests. Our results favour the newly proposed bias reduction method using the local likelihood estimator.

Item Type: Article
Uncontrolled keywords: ARMA model; generalised likelihood ratio test; local least squares; local likelihood; periodogram; spectral density
Subjects: H Social Sciences > HA Statistics
Divisions: Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science
Depositing User: Judith Broom
Date Deposited: 19 Dec 2007 18:22
Last Modified: 29 May 2012 09:26
Resource URI: http://kar.kent.ac.uk/id/eprint/600 (The current URI for this page, for reference purposes)
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