License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.GIScience.2023.56
URN: urn:nbn:de:0030-drops-189517
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2023/18951/
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Nishi, Hayato ; Yamada, Ikuho

Counter-Intuitive Effect of Null Hypothesis on Moran’s I Tests Under Heterogenous Populations (Short Paper)

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Abstract

We examine the effect of null hypothesis on spatial autocorrelation tests using Moran’s I statistic. There are two possible variable states that do not exhibit spatial autocorrelation. One is that they have the same average values in all small regions, and the other is that they are not the same, but their variations are spatially random. The second state is less restrictive than the first. Thus, it intuitively appears suitable for the null hypothesis of Moran’s I test. However, we found that it can make false discoveries more frequently than the nominal rate of the test when the first state is the true data generation process.

BibTeX - Entry

@InProceedings{nishi_et_al:LIPIcs.GIScience.2023.56,
  author =	{Nishi, Hayato and Yamada, Ikuho},
  title =	{{Counter-Intuitive Effect of Null Hypothesis on Moran’s I Tests Under Heterogenous Populations}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{56:1--56:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2023/18951},
  URN =		{urn:nbn:de:0030-drops-189517},
  doi =		{10.4230/LIPIcs.GIScience.2023.56},
  annote =	{Keywords: Moran’s I statistic, spatial autocorrelation, spatial heterogeneity, false discovery, null hypothesis}
}

Keywords: Moran’s I statistic, spatial autocorrelation, spatial heterogeneity, false discovery, null hypothesis
Collection: 12th International Conference on Geographic Information Science (GIScience 2023)
Issue Date: 2023
Date of publication: 07.09.2023

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