SEM Trees and SEM Forests  an extension of modelbased decision trees and forests to Structural Equation Models (SEM). SEM trees hierarchically split empirical data into homogeneous groups sharing similar data patterns with respect to a SEM by recursively selecting optimal predictors of these differences. SEM forests are an extension of SEM trees. They are ensembles of SEM trees each built on a random sample of the original data. By aggregating over a forest, we obtain measures of variable importance that are more robust than measures from single trees.
Package details 


Author  Andreas M. Brandmaier [aut, cre], John J. Prindle [aut] 
Maintainer  Andreas M. Brandmaier <[email protected]> 
License  GPL3 
Version  0.9.13 
Package repository  View on GitHub 
Installation 
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