sesem: Spatially explicit structural equation modeling

Structural equation modeling (SEM) is a powerful statistical approach for the testing of networks of direct and indirect theoretical causal relationships in complex datasets with intercorrelated dependent and independent variables. Here we implement a simple method for spatially explicit SEM (SE-SEM) based on the analysis of variance covariance matrices calculated across a range of lag distances. This method provides readily interpretable plots of the change in path coefficients across scale.

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