文章基本信息

标题：An asymptotic theory for spectral analysis of random fields
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作者：Soudeep Deb ; Mohsen Pourahmadi ; Wei Biao Wu 等
期刊名称：Electronic Journal of Statistics
印刷版ISSN：1935-7524
出版年度：2017
卷号：11
期号：2
页码：4297-4322
DOI：10.1214/17-EJS1326
语种：English
出版社：Institute of Mathematical Statistics
摘要：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 $\Gamma $ of $\mathbb{Z}^{d}$. Our asymptotic theory requires minimal restriction on the index set $\Gamma $. 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.