LIPIcs.GIScience.2023.56.pdf
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Counter-Intuitive Effect of Null Hypothesis on Moran’s I Tests Under Heterogenous Populations (Short Paper)
Authors
Hayato Nishi 
,
Ikuho Yamada
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Volume:
12th International Conference on Geographic Information Science (GIScience 2023)
Series: Leibniz International Proceedings in Informatics (LIPIcs)
Conference: International Conference on Geographic Information Science (GIScience) - License:
Creative Commons Attribution 4.0 International license
- Publication Date: 2023-09-07
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Hayato Nishi and Ikuho Yamada. Counter-Intuitive Effect of Null Hypothesis on Moran’s I Tests Under Heterogenous Populations (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 56:1-56:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/LIPIcs.GIScience.2023.56
https://doi.org/10.4230/LIPIcs.GIScience.2023.56
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.
Subject Classification
ACM Subject Classification
- Information systems → Geographic information systems
Keywords
- Moran’s I statistic
- spatial autocorrelation
- spatial heterogeneity
- false discovery
- null hypothesis
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References
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