Analysis, Simulation and Prediction of Multivariate Random Fields with Package Random Fields

被引:0
|
作者
Schlather, Martin [1 ]
Malinowski, Alexander [1 ]
Menck, Peter J. [2 ]
Oesting, Marco [3 ]
Strokorb, Kirstin [1 ]
机构
[1] Univ Mannheim, Mannheim, Germany
[2] Potsdam Inst Climate Impact Res, Potsdam, Germany
[3] INRA, AgroParisTech, Paris, France
来源
JOURNAL OF STATISTICAL SOFTWARE | 2015年 / 63卷 / 08期
关键词
multivariate geostatistics; bivariate Matern model; linear model of coregionalization; matrix-valued covariance function; multivariate random field; R; vector-valued field; CROSS-COVARIANCE FUNCTIONS; R PACKAGE; MODELS;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Modeling of and inference on multivariate data that have been measured in space, such as temperature and pressure, are challenging tasks in environmental sciences, physics and materials science. We give an overview over and some background on modeling with cross-covariance models. The R package RandomFields supports the simulation, the parameter estimation and the prediction in particular for the linear model of coregionalization, the multivariate Matern models, the delay model, and a spectrum of physically motivated vector valued models. An example on weather data is considered, illustrating the use of RandomFields for parameter estimation and prediction.
引用
收藏
页码:1 / 25
页数:25
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