Initial Release v0.1.0 #127
aaronpeikert
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StructuralEquationModels v0.1.0
This is a package for Structural Equation Modeling.
It is still in development.
Models you can fit include
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 and match 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 mix and match strategy also applies to gradients, where you may supply analytic gradients or opt for automatic differentiation or mix analytical and automatic differentiation.
You may consider using this package if:
The package makes use of
Registration
JuliaRegistries/General#62956
What's Changed
New Contributors
Full Changelog: https://github.com/StructuralEquationModels/StructuralEquationModels.jl/commits/v0.1.0
This discussion was created from the release Initial Release v0.1.0.
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