Higher-order accurate polyspectral estimation with flat-top lag-windows |
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Authors: | Arthur Berg Dimitris N Politis |
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Institution: | (1) Department of Statistics, University of Florida, PO Box 110339, Gainesville, FL 32611-0339, USA;(2) Department of Mathematics, University of California, San Diego, La Jolla, CA 92093-0112, USA |
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Abstract: | Improved performance in higher-order spectral density estimation is achieved using a general class of infinite-order kernels.
These estimates are asymptotically less biased but with the same order of variance as compared to the classical estimators
with second-order kernels. A simple, data-dependent algorithm for selecting the bandwidth is introduced and is shown to be
consistent with estimating the optimal bandwidth. The combination of the specialized family of kernels with the new bandwidth
selection algorithm yields a considerably improved polyspectral estimator surpassing the performances of existing estimators
using second-order kernels. Bispectral simulations with several standard models are used to demonstrate the enhanced performance
with the proposed methodology. |
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Keywords: | Bispectrum Nonparametric estimation Spectral density Time series |
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