partialDependence

plot.partialDependence

partialDependencePlot

forest

Label of the (independent) reference variable for which
partial dependence is plotted

reference.var

Label of the (dependent) model parameter for which
partial dependence is plotted

reference.param

Number of grid points for interpolating the reference.var

support

Partial dependence plot for the effect of an indepedent variable in the
dataset on the dependent outcome parameter selected. Returns a
partialDependence object that can be plotted via generic plot command.

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>).

partialDependence: Partial Dependence Plot

Description

Usage

Arguments