Bernoulli

  • Bernoulli
  • Volume 25, Number 1 (2019), 499-520.

Central limit theorem for Fourier transform and periodogram of random fields

Magda Peligrad and Na Zhang

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Abstract

In this paper, we show that the limiting distribution of the real and the imaginary part of the Fourier transform of a stationary random field is almost surely an independent vector with Gaussian marginal distributions, whose variance is, up to a constant, the field’s spectral density. The dependence structure of the random field is general and we do not impose any restrictions on the speed of convergence to zero of the covariances, or smoothness of the spectral density. The only condition required is that the variables are adapted to a commuting filtration and are regular in some sense. The results go beyond the Bernoulli fields and apply to both short range and long range dependence. They can be easily applied to derive the asymptotic behavior of the periodogram associated to the random field. The method of proof is based on new probabilistic methods involving martingale approximations and also on borrowed and new tools from harmonic analysis. Several examples to linear, Volterra and Gaussian random fields will be presented.

Article information

Source
Bernoulli, Volume 25, Number 1 (2019), 499-520.

Dates
Received: April 2017
Revised: October 2017
First available in Project Euclid: 12 December 2018

Permanent link to this document
https://projecteuclid.org/euclid.bj/1544605254

Digital Object Identifier
doi:10.3150/17-BEJ995

Mathematical Reviews number (MathSciNet)
MR3892327

Zentralblatt MATH identifier
07007215

Keywords
central limit theorem Fourier transform martingale approximation random field spectral density

Citation

Peligrad, Magda; Zhang, Na. Central limit theorem for Fourier transform and periodogram of random fields. Bernoulli 25 (2019), no. 1, 499--520. doi:10.3150/17-BEJ995. https://projecteuclid.org/euclid.bj/1544605254


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