Beyond Moran's I: Testing for Spatial Dependence Based on the Spatial Autoregressive Model

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Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder (2021, methodology): “Measuring spatial autocorrelation using Moran’s I statistic The Moran’s I statistic [41] is a measure of spatial autocorrelation measure, and can be used to rank genes by their spatially informative rank [42].”
Spatio-Temporal Data Mining (2017, methodology): “The strength of auto-correlation among ST reference points can also be measured using the Moran’s I function [Li et al. 2007a], local Moran’s I [Anselin 1995], and its ST extension [Hardisty and Klippel 2010].”
On the relationship between conditional (CAR) and simultaneous (SAR) autoregressive models (2017, background): “, which is sucient for SAR model condition S1. Note that it is possible for all ! i to be positive, even when ˆW has some zero eigenvalues ( i = 0), and thus our result is more general than that of Li et al. (2007), who only consider the case when 3 all i 6= 0. If any i 6= 0, then at least two i ”