Schlather, Martin, Malinowski, Alexander, Menck, Peter J., Oesting, Marco and Strokorb, Kirstin ![]() |
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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.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Mathematics |
Subjects: | Q Science > QA Mathematics |
Uncontrolled Keywords: | Multivariate geostatistics; Bivariate Matérn model; Linear model of coregionalization; Matrix-valued covariance function; Multivariate random field; R; Vector-valued field |
Publisher: | American Statistical Association |
ISSN: | 1548-7660 |
Date of First Compliant Deposit: | 6 January 2017 |
Date of Acceptance: | 1 October 2014 |
Last Modified: | 03 May 2023 01:34 |
URI: | https://orca.cardiff.ac.uk/id/eprint/97210 |
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