Aswi Aswi, Susanna Cramb, Earl Duncan, Kerrie Mengersen
Moran's I is commonly used to detect spatial autocorrelation in spatial data. However, Moran's I may lead to underestimating spatial dependence when used for a small number of areas. This led to the development of Modified Moran's I, which is designed to work when there are few areas. In this paper, both methods will be presented. Many R programs enable calculating Moran's I, but to date, none have been available for calculating Modified Moran's I. This paper aims to present both methods and provide the R code for calculating Modified Moran's I, with an application to a case study of dengue fever across 14 regions in Makassar, Indonesia. © 2021 Published under licence by IOP Publishing Ltd.
Statistics Department, Universitas Negeri Makassar, Makassar, Indonesia; Centre for Data Science, Queensland University of Technology, Brisbane, Australia; School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia; Centre for Healthcare Transformation, School of Public Health and Social Work, Queensland University of Technology, Australia
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