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Analysis, Simulation and Prediction of Multivariate Random Fields with PackageRandomFields

  • Martin Schlather
  • , Alexander Malinowski
  • , Peter J. Menck
  • , Marco Oesting
  • , Kirstin Strokorb
  • University of Mannheim
  • Potsdam Institute for Climate Impact Research
  • AgroParisTech/INRA

Research output: Contribution to journalArticlepeer-review

163   Link opens in a new tab Citations (SciVal)

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.
Original languageEnglish
JournalJournal of Statistical Software
Volume63
Issue number8
DOIs
Publication statusPublished - 10 Feb 2015

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