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: | 0.9.14 |
Depends: | R (≥ 2.10), OpenMx (≥ 2.6.9) |
Imports: | bitops, sets, digest, rpart, rpart.plot (≥ 3.0.6), parallel, plotrix, cluster, stringr, matrixcalc, expm, ggplot2, tidyr, matrixStats, methods, MASS, mvtnorm |
Suggests: | lavaan, knitr, rmarkdown |
Published: | 2020-01-07 |
Author: | Andreas M. Brandmaier [aut, cre], John J. Prindle [aut], Manuel Arnold [aut] |
Maintainer: | Andreas M. Brandmaier <andy at brandmaier.de> |
License: | GPL-3 |
NeedsCompilation: | no |
Materials: | README NEWS |
In views: | Psychometrics |
CRAN checks: | semtree results |
Reference manual: | semtree.pdf |
Vignettes: |
constraints getting-started |
Package source: | semtree_0.9.14.tar.gz |
Windows binaries: | r-devel: semtree_0.9.14.zip, r-release: semtree_0.9.14.zip, r-oldrel: semtree_0.9.14.zip |
macOS binaries: | r-release: semtree_0.9.14.tgz, r-oldrel: semtree_0.9.14.tgz |
Old sources: | semtree archive |
Please use the canonical form https://CRAN.R-project.org/package=semtree to link to this page.