symSEM-package: A collection of functions for symbolic computation using...
In symSEM: Symbolic Computation for Structural Equation Models
symSEM-package R Documentation
A collection of functions for symbolic computation using 'caracas'
package for structural equation models and other statistical analyses.
Among its features is the ability to calculate the model-implied
covariance (and correlation) matrix and the sampling covariance matrix of
variable functions using the delta method.
Description
A collection of functions for symbolic computation using 'caracas'
package for structural equation models and other statistical analyses.
Among its features is the ability to calculate the model-implied
covariance (and correlation) matrix and the sampling covariance matrix of
variable functions using the delta method.
symSEM documentation built on May 31, 2023, 9:12 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| symSEM-package | R Documentation |
A collection of functions for symbolic computation using 'caracas' package for structural equation models and other statistical analyses. Among its features is the ability to calculate the model-implied covariance (and correlation) matrix and the sampling covariance matrix of variable functions using the delta method.
Description
A collection of functions for symbolic computation using 'caracas' package for structural equation models and other statistical analyses. Among its features is the ability to calculate the model-implied covariance (and correlation) matrix and the sampling covariance matrix of variable functions using the delta method.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.