掩饰
发表于 2025-3-21 19:02:39
书目名称Random Fields for Spatial Data Modeling影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK0821046<br><br> <br><br>书目名称Random Fields for Spatial Data Modeling影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK0821046<br><br> <br><br>书目名称Random Fields for Spatial Data Modeling网络公开度<br> http://impactfactor.cn/at/?ISSN=BK0821046<br><br> <br><br>书目名称Random Fields for Spatial Data Modeling网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK0821046<br><br> <br><br>书目名称Random Fields for Spatial Data Modeling被引频次<br> http://impactfactor.cn/tc/?ISSN=BK0821046<br><br> <br><br>书目名称Random Fields for Spatial Data Modeling被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK0821046<br><br> <br><br>书目名称Random Fields for Spatial Data Modeling年度引用<br> http://impactfactor.cn/ii/?ISSN=BK0821046<br><br> <br><br>书目名称Random Fields for Spatial Data Modeling年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK0821046<br><br> <br><br>书目名称Random Fields for Spatial Data Modeling读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK0821046<br><br> <br><br>书目名称Random Fields for Spatial Data Modeling读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK0821046<br><br> <br><br>
可互换
发表于 2025-3-21 21:12:43
http://reply.papertrans.cn/83/8211/821046/821046_2.png
intercede
发表于 2025-3-22 03:02:33
Additional Topics of Random Field Modeling, types of anisotropy, and the description of the joint dependence of random fields at more than two points. Ergodicity, isotropy and anisotropy are properties that have significant practical interest for the modeling of spatial data. On the other hand, the joint .-point dependence is a more advanced
使高兴
发表于 2025-3-22 08:31:42
Geometric Properties of Random Fields,ian random functions is to a large extent determined by the mean and the two-point correlation functions. The classical text on the geometry of random fields is the book written by Robert Adler [.]. The basic elements of random field geometry are contained in the technical report by Abrahamsen [.].
Condyle
发表于 2025-3-22 10:03:57
http://reply.papertrans.cn/83/8211/821046/821046_5.png
APRON
发表于 2025-3-22 13:45:31
Random Fields Based on Local Interactions,ective is useful, because it can lead to computationally efficient methods for spatial prediction, while it is also related with Markovian random fields. In addition, it enables the calculation of new forms of covariance functions and provides a link with ..
名次后缀
发表于 2025-3-22 20:31:46
http://reply.papertrans.cn/83/8211/821046/821046_7.png
Biomarker
发表于 2025-3-22 21:46:14
Spatial Prediction Fundamentals,ble spatial model and the “best” values for the parameters of the model. Parameter estimation is not necessary for certain simple deterministic models (e.g., nearest neighbor method), since such models do not involve any free parameters. . is then used to choose the “optimal model” (based on some sp
植物茂盛
发表于 2025-3-23 02:56:57
More on Spatial Prediction,h generalizations include the application of ordinary kriging to . that can handle non-stationary data, as well as the methods of . and . that incorporate deterministic trends in the linear prediction equation [.]. . allows combining multivariate information in the prediction equations. Various . of
嬉耍
发表于 2025-3-23 06:25:44
http://reply.papertrans.cn/83/8211/821046/821046_10.png