A TEST FOR STATIONARITY OF SPATIO-TEMPORAL RANDOM FIELDS ON PLANAR AND SPHERICAL DOMAINS

被引：25

作者：

Jun, Mikyoung ^{[1
]}

Genton, Marc G. ^{[1
]}

机构：

[1] Texas A&M Univ, Dept Stat, College Stn, TX 77843 USA

来源：

STATISTICA SINICA | 2012年 / 22卷 / 04期

关键词：

Asymptotic normality; axial symmetry; climate model output; increasing domain asymptotics; inference; pacific wind data; stationarity; CROSS-COVARIANCE FUNCTIONS; MULTIVARIATE RANDOM-FIELDS; SPACE; SEPARABILITY; MODELS;

D O I：

10.5705/ss.2010.251

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

A formal test for weak stationarity of spatial and spatio-temporal random fields is proposed. We consider the cases where the spatial domain is planar or spherical, and we do not require distributional assumptions for the random fields. The method can be applied to univariate or to multivariate random fields. Our test is based on the asymptotic normality of certain statistics that are functions of estimators of covariances at certain spatial and temporal lags under weak stationarity. Simulation results for spatial as well as spatio-temporal cases on the two types of spatial domains are reported. We describe the results of testing the stationarity of Pacific wind data, and of testing the axial symmetry of climate model errors for surface temperature using the NOAA GFDL model outputs and the observations from the Climate Research Unit in East Anglia and the Hadley Centre.

引用

页码：1737 / 1764

页数：28

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