Analysis, simulation and prediction of multivariate random fields with package randomfields

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Date
2015
Volume
63
Issue
8
Journal
Series Titel
Book Title
Publisher
Los Angeles, Calif. : UCLA, Dept. of Statistics
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Abstract

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 crosscovariance models. The R package RandomFields supports the simulation, the parameter estimation and the prediction in particular for the linear model of coregionalization, the multivariate Matérn 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.

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Keywords
Bivariate Matérn model, Linear model of coregionalization, Matrix-valued covariance function, Multivariate geostatistics, Multivariate random field, R, Vector-valued field
Citation
Schlather, M., Malinowski, A., Menck, P. J., Oesting, M., & Strokorb, K. (2015). Analysis, simulation and prediction of multivariate random fields with package randomfields. 63(8). https://doi.org//10.18637/jss.v063.i08
License
CC BY 3.0 Unported