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cvsem  

SEM Model Comparison with K-Fold Cross-Validation
View on CRAN: Click here


Download and install cvsem package within the R console
Install from CRAN:
install.packages("cvsem")

Install from Github:
library("remotes")
install_github("cran/cvsem")

Install by package version:
library("remotes")
install_version("cvsem", "1.0.0")



Attach the package and use:
library("cvsem")
Maintained by
Anna Wysocki
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-08-13
Latest Update: 2022-08-13
Description:
The goal of 'cvsem' is to provide functions that allow for comparing Structural Equation Models (SEM) using cross-validation. Users can specify multiple SEMs using 'lavaan' syntax. 'cvsem' computes the Kullback Leibler (KL) Divergence between 1) the model implied covariance matrix estimated from the training data and 2) the sample covariance matrix estimated from the test data described in Cudeck, Robert & Browne (1983) . The KL Divergence is computed for each of the specified SEMs allowing for the models to be compared based on their prediction errors.
How to cite:
Anna Wysocki (2022). cvsem: SEM Model Comparison with K-Fold Cross-Validation. R package version 1.0.0, https://cran.r-project.org/web/packages/cvsem. Accessed 22 Dec. 2024.
Previous versions and publish date:
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Complete documentation for cvsem
Functions, R codes and Examples using the cvsem R package
Some associated functions: KL_divergence . cvgather . cvsem . dot-lavaan_vars . fd . gls . print.cvsem . 
Some associated R codes: DistanceMetrics.R . createFolds.R . cvgather.R . cvsem.R . lavaanWrapper.R . print.R .  Full cvsem package functions and examples
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