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A New Perspective on Moran’s Coefficient: Revisited

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  • Hiroshi Yamada

    (Graduate School of Humanities and Social Sciences, Hiroshima University, 1-2-1 Kagamiyama, Higashihiroshima 739-8525, Japan)

Abstract

Moran’s I (Moran’s coefficient) is one of the most prominent measures of spatial autocorrelation. It is well known that Moran’s I has a representation that is similar to a Fourier series and is therefore useful for characterizing spatial data. However, the representation needs to be modified. This paper contributes to the literature by showing the necessary modification and presenting some further results. In addition, we provide the required MATLAB/GNU Octave and R user-defined functions.

Suggested Citation

  • Hiroshi Yamada, 2024. "A New Perspective on Moran’s Coefficient: Revisited," Mathematics, MDPI, vol. 12(2), pages 1-14, January.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:2:p:253-:d:1318151
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    References listed on IDEAS

    as
    1. Daisuke Murakami & Daniel Griffith, 2015. "Random effects specifications in eigenvector spatial filtering: a simulation study," Journal of Geographical Systems, Springer, vol. 17(4), pages 311-331, October.
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