New Validity Conditions for the Multivariate Matérn Coregionalization Model, with an Application to Exploration Geochemistry

Xavier Emery, Emilio Porcu, Philip White

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

This paper addresses the problem of finding parametric constraints that ensure the validity of the multivariate Matérn covariance for modeling the spatial correlation structure of coregionalized variables defined in an Euclidean space. To date, much attention has been given to the bivariate setting, while the multivariate setting has been explored to only a limited extent. The existing conditions often imply severe restrictions on the upper bounds for the collocated correlation coefficients, which makes the multivariate Matérn model appealing for the case of weak spatial cross-dependence only. We provide a collection of sufficient validity conditions for the multivariate Matérn covariance that allows for more flexible parameterizations than those currently available, and prove that one can attain considerably higher upper bounds for the collocated correlation coefficients in comparison with our competitors. We conclude with an illustration on a trivariate geochemical data set and show that our enlarged parametric space yields better fitting performances.

Original languageBritish English
Pages (from-to)1043-1068
Number of pages26
JournalMathematical Geosciences
Volume54
Issue number6
DOIs
StatePublished - Aug 2022

Keywords

  • Conditionally negative semidefinite matrices
  • Coregionalization modeling
  • Multivariate covariance function
  • Spatial cross-correlation
  • Vector random fields

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