proximity

plot.proximity

plot.semforest.proximity

A <code><a rd-options="" href="/link/semforest?package=semtree&version=0.9.16" data-mini-rdoc="semtree::semforest">semforest</a></code> object.

forest

A dataset to compute proximity values for.

dataset

Missingness accounted for. (0 = no, 1 = yes)

type

Boolean marker to compute aggregate proximity scores.

aggregate

&#8230;

A <code><a rd-options="" href="/link/semforest?package=semtree&version=0.9.16" data-mini-rdoc="semtree::semforest">semforest</a></code> process to represent proportion of trees where
each case are in the same leaf nodes. The values are bounded (0,1), where
higher values are closer in proximity.

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>).

Andreas M. Brandmaier andy@brandmaier.de

semtree

Recursive Partitioning for Structural Equation Models

Andreas M. Brandmaier 

John J. Prindle 

Manuel Arnold 

proximity function

A <code><a rd-options='' href='semforest'>semforest</a></code> object.

A <code><a rd-options='' href='semforest'>semforest</a></code> process to represent proportion of trees where
each case are in the same leaf nodes. The values are bounded (0,1), where
higher values are closer in proximity.

proximity: SEM Forest Case Proximity

Description

Usage

Arguments

Value

References

See Also