SEM Trees and SEM Forests – an extension of model-based 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.
|Depends:||OpenMx (≥ 2.6.9)|
|Imports:||bitops, sets, digest, rpart, rpart.plot, parallel|
|Author:||Andreas M. Brandmaier [aut, cre], John J. Prindle [aut]|
|Maintainer:||Andreas M. Brandmaier <andy at brandmaier.de>|
|CRAN checks:||semtree results|
|Windows binaries:||r-devel: semtree_0.9.10.zip, r-release: semtree_0.9.10.zip, r-oldrel: semtree_0.9.10.zip|
|OS X El Capitan binaries:||r-release: semtree_0.9.10.tgz|
|OS X Mavericks binaries:||r-oldrel: semtree_0.9.10.tgz|
|Old sources:||semtree archive|
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