DESCRIPTION

Package: semtree
Type: Package
Title: Recursive Partitioning for Structural Equation Models
Authors@R: c(person("Andreas M. Brandmaier", email="andy@brandmaier.de", role=c("aut","cre")), person("John J. Prindle", email="jprindle@usc.edu",role=c("aut")),person("Manuel Arnold", email="arnoldmz@hu-berlin.de",role=c("aut")),person("Caspar J. Van Lissa", email="C.J.vanLissa@uu.nl",role=c("aut")))
Author: Andreas M. Brandmaier [aut, cre],
    John J. Prindle [aut],
	Manuel Arnold [aut],
	Caspar J. Van Lissa [aut]
Maintainer: Andreas M. Brandmaier <andy@brandmaier.de>
Depends:
    R (>= 2.10),
    OpenMx (>= 2.6.9),
Imports:
    rpart,
    rpart.plot (>= 3.0.6),
    lavaan,
    cluster,
    ggplot2,
    tidyr,
    dplyr,
    methods,
    strucchange,
    sandwich,
    zoo,
    crayon,
    clisymbols,
    future.apply,
    data.table,
    expm,
    gridBase
Suggests:
    knitr,
    rmarkdown,
    viridis,
    MASS,
    psychTools,
    testthat,
    future,
    ctsemOMX
Description: 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 each 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. A description of the method was published by
    Brandmaier, von Oertzen, McArdle, & Lindenberger (2013) <doi:10.1037/a0030001> 
    and Arnold, Voelkle, & Brandmaier (2020) <doi:10.3389/fpsyg.2020.564403>.
License: GPL-3
Encoding: UTF-8
LazyLoad: yes
Version: 0.9.20
Date: 2024-03-25
RoxygenNote: 7.2.3
VignetteBuilder: knitr
BugReports: https://github.com/brandmaier/semtree/issues
URL: https://github.com/brandmaier/semtree
Language: en-US