structuralequationmodels jl

We have hosted the application structuralequationmodels jl in order to run this application in our online workstations with Wine or directly.

Quick description about structuralequationmodels jl:

This is a package for Structural Equation Modeling in development. It is written for extensibility, that is, you can easily define your own objective functions and other parts of the model. At the same time, it is (very) fast. We provide fast objective functions, gradients, and for some cases hessians as well as approximations thereof. As a user, you can easily define custom loss functions. For those, you can decide to provide analytical gradients or use finite difference approximation / automatic differentiation. You can choose to mix loss functions natively found in this package and those you provide. In such cases, you optimize over a sum of different objectives (e.g. ML + Ridge). This strategy also applies to gradients, where you may supply analytic gradients or opt for automatic differentiation or mixed analytical and automatic differentiation. You may consider using this package if you need extensibility and/or speed, and if you want to extend SEM.

Features:

• Linear SEM that can be specified in RAM notation
• ML, GLS and FIML estimation
• Ridge Regularization
• Multigroup SEM
• Sums of arbitrary loss functions (everything the optimizer can handle)
• Extend SEM (e.g. add a new objective function)

Programming Language: Julia.
Categories: