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
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页码：1 / 42
页数：42
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