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Rethinking the null hypothesis in significant colocation pattern mining of spatial flows

Author

Listed:
  • Mengjie Zhou

    (Hunan Normal University
    Hunan Key Laboratory of Geospatial Big Data Mining and Application)

  • Mengjie Yang

    (Hunan Normal University)

  • Tinghua Ai

    (Wuhan University)

  • Jiannan Cai

    (The Chinese University of Hong Kong)

  • Zhe Chen

    (Hunan Normal University)

Abstract

Spatial flows represent spatial interactions or movements. Mining colocation patterns of different types of flows may uncover the spatial dependences and associations among flows. Previous studies proposed a flow colocation pattern mining method and established a significance test under the null hypothesis of independence for the results. In fact, the definition of the null hypothesis is crucial in significance testing. Choosing an inappropriate null hypothesis may lead to misunderstandings about the spatial interactions between flows. In practice, the overall distribution patterns of different types of flows may be clustered. In these cases, the null hypothesis of independence will result in unconvincing results. Thus, considering the overall spatial pattern of flows, in this study, we changed the null hypothesis to random labeling to establish the statistical significance of flow colocation patterns. Furthermore, we compared and analyzed the impacts of different null hypotheses on flow colocation pattern mining through synthetic data tests with different preset patterns and situations. Additionally, we used empirical data from ride-hailing trips to show the practicality of the method.

Suggested Citation

  • Mengjie Zhou & Mengjie Yang & Tinghua Ai & Jiannan Cai & Zhe Chen, 2024. "Rethinking the null hypothesis in significant colocation pattern mining of spatial flows," Journal of Geographical Systems, Springer, vol. 26(3), pages 375-405, July.
    • Handle: RePEc:kap:jgeosy:v:26:y:2024:i:3:d:10.1007_s10109-024-00439-y
    DOI: 10.1007/s10109-024-00439-y
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    Keywords

    Colocation pattern; Spatial flow; Statistical significance test; Null hypothesis; Random labeling;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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