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Information Consistency-Based Measures for Spatial Stratified Heterogeneity

Bibliographic Data

ID3775711
AuthorsHexiang Bai (0000-0003-3098-9609, Shanxi University), Hui Wang (0000-0001-5109-8691, Shanxi University), Deyu Li (0000-0002-9154-6302, Shanxi University), Yong Ge (0000-0002-9524-7908, Chinese Academy of Sciences)
Year2023
Volume113
Issue10
Pages2512-2524
Publication date2023-11-26
Open AccessNo
TypeARTICLE
VenueAnnals of the American Association of Geographers (JOURNAL)
Journal identifiersISSN: 2469-4452 • E-ISSN: 2469-4460
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/24694452.2023.2223700
OpenAlexW4385213917
LanguageEN
Citations received3
References cited54

As a typical form of spatial heterogeneity, spatial stratified heterogeneity is widely observed in geographical phenomena. Although the q statistic provides a measure of spatial stratified heterogeneity using variance differences, it is not suitable for nominal target variables and neglects information differences between strata at higher order moments. Based on the mutual information and relative entropy between variables, two spatial stratified heterogeneity measures are proposed for nominal and continuous target variables, respectively. Permutation tests are then used to determine their statistical significance. The proposed measures are suitable for either nominal or continuous target variables. They make no assumptions regarding the distribution of target variables, and return a value of zero only when the distribution of the target variable is independent of the explanatory variable. Experiments on five illustrative data sets and three publicly accessible data sets show that the proposed measures are consistent with the q statistic and can detect the existence of spatial stratified heterogeneity when the q statistic fails, so long as there are significant differences between the distributions in different strata

Econometrics · Kullback–Leibler divergence · Spatial analysis · Spatial heterogeneity · Statistic · Statistics · Land Use and Ecosystem Services · Mathematics · Regional Economic and Spatial Analysis · Spatial and Panel Data Analysis

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Citations per year1.5
Citation span2024 - 2025 (2)
Highly citedNo

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