An asymptotic theory for spectral analysis of random fields Academic Article uri icon

abstract

  • 2017, Institute of Mathematical Statistics. All rights reserved. For a general class of stationary random fields we study asymptotic properties of the discrete Fourier transform (DFT), periodogram, parametric and nonparametric spectral density estimators under an easily verifiable short-range dependence condition expressed in terms of functional dependence measures. We allow irregularly spaced data which is indexed by a subset of Zd. Our asymptotic theory requires minimal restriction on the index set . Asymptotic normality is derived for kernel spectral density estimators and the Whittle estimator of a parameterized spectral density function. We also develop asymptotic results for a covariance matrix estimate.

published proceedings

  • ELECTRONIC JOURNAL OF STATISTICS

author list (cited authors)

  • Deb, S., Pourahmadi, M., & Wu, W. B.

citation count

  • 8

complete list of authors

  • Deb, Soudeep||Pourahmadi, Mohsen||Wu, Wei Biao

publication date

  • January 1, 2017 11:11 AM