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Modeling distances between humans using Taylor’s law and geometric probability

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  • Joel E. Cohen
  • Daniel Courgeau

Abstract

Taylor’s law states that the variance of the distribution of distance between two randomly chosen individuals is a power function of the mean distance. It applies to the distances between two randomly chosen points in various geometric shapes, subject to a few conditions. In Réunion Island and metropolitan France, at some spatial scales, the empirical frequency distributions of inter-individual distances are predicted accurately by the theoretical frequency distributions of inter-point distances in models of geometric probability under a uniform distribution of points. When these models fail to predict the empirical frequency distributions of inter-individual distances, they provide baselines against which to highlight the spatial distribution of population concentrations.

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  • Joel E. Cohen & Daniel Courgeau, 2017. "Modeling distances between humans using Taylor’s law and geometric probability," Mathematical Population Studies, Taylor & Francis Journals, vol. 24(4), pages 197-218, October.
    • Handle: RePEc:taf:mpopst:v:24:y:2017:i:4:p:197-218
    DOI: 10.1080/08898480.2017.1289049
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    1. repec:cai:popine:popu_p1970_25n6_1182 is not listed on IDEAS
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    Cited by:

    1. Solal Lellouche & Marc Souris, 2019. "Distribution of Distances between Elements in a Compact Set," Stats, MDPI, vol. 3(1), pages 1-15, December.

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