Estimation of a nonparametric regression spectrum for multivariate time series
AbstractEstimation of a nonparametric regression spectrum based on the periodogram is considered. Neither trend estimation nor smoothing of the periodogram are required. Alternatively, for cases where spectral estimation of phase shifts fails and the shift does not depend on frequency, a time domain estimator of the lag-shift is defined. Asymptotic properties of the frequency and time domain estimators are derived. Simulations and a data example illustrate the methods.
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Bibliographic InfoPaper provided by Center of Finance and Econometrics, University of Konstanz in its series CoFE Discussion Paper with number 07-12.
Length: 31 pages
Date of creation: 01 Dec 2007
Date of revision:
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-08-06 (All new papers)
- NEP-ECM-2008-08-06 (Econometrics)
- NEP-ETS-2008-08-06 (Econometric Time Series)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Ori Rosen & David S. Stoffer, 2007. "Automatic estimation of multivariate spectra via smoothing splines," Biometrika, Biometrika Trust, vol. 94(2), pages 335-345.
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