semtree: Recursive Partitioning for Structural Equation Models

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.

Version: 0.9.12
Depends: OpenMx (≥ 2.6.9)
Imports: bitops, sets, digest, rpart, rpart.plot, parallel, plotrix, cluster
Suggests: lavaan
Published: 2018-02-13
Author: Andreas M. Brandmaier [aut, cre], John J. Prindle [aut]
Maintainer: Andreas M. Brandmaier <andy at brandmaier.de>
License: GPL-3
NeedsCompilation: no
Materials: README NEWS
In views: Psychometrics
CRAN checks: semtree results

Downloads:

Reference manual: semtree.pdf
Package source: semtree_0.9.12.tar.gz
Windows binaries: r-devel: semtree_0.9.12.zip, r-release: semtree_0.9.12.zip, r-oldrel: semtree_0.9.12.zip
OS X El Capitan binaries: r-release: semtree_0.9.12.tgz
OS X Mavericks binaries: r-oldrel: semtree_0.9.11.tgz
Old sources: semtree archive

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