期刊
ANNALS OF APPLIED STATISTICS
卷 2, 期 4, 页码 1271-1289出版社
INST MATHEMATICAL STATISTICS
DOI: 10.1214/08-AOAS183
关键词
Nonstationary covariance function; processes on spheres; TOMS ozone data; fast Fourier transform
资金
- National Science Foundation [ATM-0620624]
With the widespread availability of satellite-based instruments, many geophysical processes are measured on a global scale and they often show strong nonstationarity in the covariance structure. In this paper we present a flexible class of parametric covariance models that can capture the nonstationarity, in global data, especially strong dependency of covariance structure on latitudes. We apply the Discrete Fourier Transform to data on regular grids, which enables us to calculate the exact likelihood for large data sets. Our covariance model is applied to global total column ozone level data on a given day. We discuss how our covariance model compares with some existing models.
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