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Adaptive semiparametric estimation in the presence of autocorrelation of unknown form

Hidalgo, Javier (1992) Adaptive semiparametric estimation in the presence of autocorrelation of unknown form. Journal of Time Series Analysis, 13 (1). pp. 47-78. ISSN 0143-9782

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Identification Number: 10.1111/j.1467-9892.1992.tb00094.x

Abstract

In a time series regression model the residual autoregression function is an unknown, possibly non-linear, function. It is estimated by non-parametric kernel regression. The resulting least-squares estimate of the regression function is shown to be adapative, in the sense of having the same asymptotic distribution, to first order, as estimates based on knowledge of the autoregression function. Also, a Monte Carlo experiment about the behaviour of the estimator is described.

Item Type: Article
Official URL: http://www.blackwellpublishing.com/journal.asp?ref...
Additional Information: © 1992 American Mathematical Society
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics
Sets: Departments > Economics
Research centres and groups > Suntory and Toyota International Centres for Economics and Related Disciplines (STICERD)
Date Deposited: 18 Apr 2011 12:07
Last Modified: 18 Apr 2011 12:07
URI: http://eprints.lse.ac.uk/id/eprint/35712

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