Name
Abstract | ||
|---|---|---|
Modeling of spatio-temporal processes is critical in many fields such as environmental sciences, meteorology, hydrology and reservoir engineering. The variogram is an important correlation measure in geostatistics and a useful tool for spatial or spatio-temporal modeling. Although many space-time covariance/variogram models are available, in practice,the generalized product-sum model is most widely used. The theoretical aspects of the generalized product-sum variogram model have been presented in other papers. However, the dissemination of software that brings the generalized product-sum variogram model to a wider group of users is undoubtedly desirable. In this paper, we describe an R routine for “spatio-temporal kriging” with hole effects, and appropriate space-time search neighborhoods. An application to ozone pollutants in an area of five counties of the US is presented. The experimental results show that the spatio-temporal random field provides more information than the purely spatial random field, because the accuracy of interpolation has been improved. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/s12145-014-0195-x | Earth Science Informatics |
Keywords | Field | DocType |
Space-time variogram, Product-sum model, Spatio-temporal kriging, Computational aspects | Reservoir engineering,Kriging,Variogram,Data mining,Random field,Computer science,Interpolation,Software,Geostatistics,Covariance | Journal |
Volume | Issue | ISSN |
8 | 3 | 1865-0481 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
2 | ||