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The cgeostat Software for Analyzing Complex-Valued Random Fields

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  • de Iaco, Sandra

Abstract

Given a vectorial data set in two dimensions, a representation on a complex domain is often convenient. This representation is rarely considered in geostatistics, although interesting applications can be found in environmental sciences and meteorology (e.g., for wind fields). In such a case, some computational difficulties are related to the lack of software for estimating and modeling a complex covariance function, for predicting complex variables as well as for representing the output results. In this paper, the new Fortran software cgeostat for geostatistical analysis of complex-valued random fields is presented and an application is demonstrated.

Suggested Citation

  • de Iaco, Sandra, 2017. "The cgeostat Software for Analyzing Complex-Valued Random Fields," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i05).
    • Handle: RePEc:jss:jstsof:v:079:i05
    DOI: http://hdl.handle.net/10.18637/jss.v079.i05
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    References listed on IDEAS

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    Cited by:

    1. De Iaco, S., 2023. "Spatio-temporal generalized complex covariance models based on convolution," Computational Statistics & Data Analysis, Elsevier, vol. 183(C).
    2. Sandra De Iaco, 2023. "Families of complex‐valued covariance models through integration," Environmetrics, John Wiley & Sons, Ltd., vol. 34(3), May.

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