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Some Aspects of Multivariate Geostatistics

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Advances in Classification and Data Analysis

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Abstract

Cokriging allows the use of data on correlated variables in order to enhance the estimation of a primary variable or more generally to enhance the estimation of all variables. However, in order to apply the estimation procedure, some problems must be solved: the variogram matrix must be conditionally negative definite and it is necessary to model the cross-variogram. The aim of this paper is to present a flexible solution in order to solve the mentioned problems. A case study has been presented.

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References

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Author information

Authors and Affiliations

  1. Facoltà di Economia, Università degli Studi di Chieti, Via dei Vestini, 66013, Chieti, Italy

    Sandra De Iaco

  2. Facoltà di Economia, Università degli Studi di Lecce, Via per Monteroni, Ecotekne, 73100, Lecce, Italy

    Donato Posa

Authors
  1. Sandra De Iaco
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  2. Donato Posa
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Editor information

Editors and Affiliations

  1. Department SEFEMEQ, University of Rome “Tor Vergata”, Via di Tor Vergata, 00133, Rome, Italy

    Simone Borra

  2. Department SEGeS, University of Molise, Via de Sanctis, 86100, Campobasso, Italy

    Roberto Rocci

  3. Department Statistica, Probabilità e Statistiche Applicate, University of Rome “La Sapienza”, Piazza le Aldo Moro, 00185, Rome, Italy

    Maurizio Vichi

  4. University of Mannheim, 68131, Mannheim, Germany

    Martin Schader (Lehrstuhl für Wirtschaftsinformatik III Schloß) (Lehrstuhl für Wirtschaftsinformatik III Schloß)

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© 2001 Springer-Verlag Berlin Heidelberg

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Iaco, S.D., Posa, D. (2001). Some Aspects of Multivariate Geostatistics. In: Borra, S., Rocci, R., Vichi, M., Schader, M. (eds) Advances in Classification and Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-59471-7_39

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  • DOI: https://doi.org/10.1007/978-3-642-59471-7_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41488-9

  • Online ISBN: 978-3-642-59471-7

  • eBook Packages: Springer Book Archive

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