covatest: An R Package for Selecting a Class of Space-Time Covariance Functions

被引：15

作者：

Cappello, Claudia ^{[1
]}

De Iaco, Sandra ^{[1
]}

Posa, Donato ^{[1
]}

机构：

[1] Univ Salento, Dept Management Econ Math & Stat, I-73100 Lecce, Italy

来源：

JOURNAL OF STATISTICAL SOFTWARE | 2020年 / 94卷 / 01期

关键词：

space-time covariance functions; symmetry; separability; type of non-separability; test on classes of space-time covariance functions; STRICT POSITIVE DEFINITENESS; RANDOM-FIELDS; FORTRAN PROGRAMS; MODELS; NONSEPARABILITY; PREDICTION; PRODUCT; GSTAT;

D O I：

10.18637/jss.v094.i01

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Although a very rich list of classes of space-time covariance functions exists, specific tools for selecting the appropriate class for a given data set are needed. Thus, the main topic of this paper is to present the new R package, covatest, which can be used for testing some characteristics of a covariance function, such as symmetry, separability and type of non-separability, as well as for testing the adequacy of some classes of space-time covariance models. These last aspects can be relevant for choosing a suitable class of covariance models. The proposed results have been applied to an environmental case study.

引用

页码：1 / 42

页数：42

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