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Modeling and Exploring Multivariate Spatial Variation: A Test Procedure for Isotropy of Multivariate Spatial Data

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  • Jona-Lasinio, Giovanna

Abstract

In this paper an exploratory technique based on the diagonalization of cross-variogram matrices is described. Through the definition of a model for the analysis and simulation of multivariate spatial data, a test procedure for the assumption of isotropy of multivariate spatial data is proposed. Applications to simulated and real data are reported.

Suggested Citation

  • Jona-Lasinio, Giovanna, 2001. "Modeling and Exploring Multivariate Spatial Variation: A Test Procedure for Isotropy of Multivariate Spatial Data," Journal of Multivariate Analysis, Elsevier, vol. 77(2), pages 295-317, May.
    • Handle: RePEc:eee:jmvana:v:77:y:2001:i:2:p:295-317
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    Cited by:

    1. Yongtao Guan & Michael Sherman & James A. Calvin, 2006. "Assessing Isotropy for Spatial Point Processes," Biometrics, The International Biometric Society, vol. 62(1), pages 119-125, March.
    2. Lara Fontanella & Luigi Ippoliti, 2003. "Dynamic models for space-time prediction via Karhunen-Loève expansion," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 12(1), pages 61-78, February.

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