make_sem_ram: Make a RAM (Reticular Action Model) from a SEM (structural...

In tinyVAST: Multivariate Spatio-Temporal Models using Structural Equations

Make a RAM (Reticular Action Model) from a SEM (structural equation model)

Description

make_sem_ram converts SEM arrow notation to ram describing SEM parameters

Usage

make_sem_ram(sem, variables, quiet = FALSE, covs = variables)

Arguments

sem	structural equation model structure, passed to either specifyModel or specifyEquations and then parsed to control the set of path coefficients and variance-covariance parameters
variables	A character vector listing the set of variables
quiet	if FALSE, the default, then the number of input lines is reported and a message is printed suggesting that specifyEquations or cfa be used.
covs	optional: a character vector of one or more elements, with each element giving a string of variable names, separated by commas. Variances and covariances among all variables in each such string are added to the model. For confirmatory factor analysis models specified via cfa, covs defaults to all of the factors in the model, thus specifying all variances and covariances among these factors. Warning: covs="x1, x2" and covs=c("x1", "x2") are not equivalent: covs="x1, x2" specifies the variance of x1, the variance of x2, and their covariance, while covs=c("x1", "x2") specifies the variance of x1 and the variance of x2 but not their covariance.

Value

An S3-class "sem_ram" containing:

model

Output from specifyEquations or specifyModel that defines paths and parameters

ram

reticular action module (RAM) describing dependencies

tinyVAST documentation built on April 4, 2025, 2:43 a.m.