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

共 50 条

[21] Mortality risk assessment through stationary space-time covariance functions
Martinez-Ruiz, F.
Mateu, J.
Montes, F.
Porcu, E.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2010, 24 (04) : 519 - 526
[22] Space-time covariance models on networks
Tang, Jun
Zimmerman, Dale
ELECTRONIC JOURNAL OF STATISTICS, 2024, 18 (01): : 490 - 514
[23] Space-Time Covariance Structures and Models
Chen, Wanfang
Genton, Marc G.
Sun, Ying
ANNUAL REVIEW OF STATISTICS AND ITS APPLICATION, VOL 8, 2021, 2021, 8 : 191 - 215
[24] Contours and dimple for the Gneiting class of space-time correlation functions
Cuevas, F.
Porcu, E.
Bevilacqua, M.
BIOMETRIKA, 2017, 104 (04) : 995 - 1001
[25] On the robustness of space-time coding techniques based on a general space-time covariance model
Younkins, LT
Su, WF
Liu, KJR
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2006, 55 (01) : 219 - 233
[26] ETAS: An R Package for Fitting the Space-Time ETAS Model to Earthquake Data
Jalilian, Abdollah
JOURNAL OF STATISTICAL SOFTWARE, 2019, 88 (CN1): : 1 - 39
[27] SAMPLE SPACE-TIME COVARIANCE MATRIX ESTIMATION
Delaosa, Connor
Pestana, Jennifer
Goddard, Nicholas J.
Somasundaram, Samuel
Weiss, Stephan
2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2019, : 8033 - 8037
[28] Separable approximations of space-time covariance matrices
Genton, Marc G.
ENVIRONMETRICS, 2007, 18 (07) : 681 - 695
[29] Quasi-arithmetic means of covariance functions with potential applications to space-time data
Porcu, Emilio
Mateu, Jorge
Christakos, George
JOURNAL OF MULTIVARIATE ANALYSIS, 2009, 100 (08) : 1830 - 1844
[30] Weighted composite likelihood-based tests for space-time separability of covariance functions
M. Bevilacqua
J. Mateu
E. Porcu
H. Zhang
A. Zini
Statistics and Computing, 2010, 20 : 283 - 293

← 1 2 3 4 5 →