Two methods are currently in use for specifying SEM models in scripts. The first centers around specifying the matrices that define the covariance and mean structure of the manifest and latent variables. The second method is based on path analysis and uses a compact specification for the paths and variables in a path diagram. In the end, both of these methods produce a set of matrix equations that are used as an objective function (sometimes called a cost function) that is optimized in order to find parameters such that the objective function is at a minimum. Popular objective functions include maximum likelihood and several variants of least squares.
