StructuralEquationModels
A fast and flexible Structural Equation Modelling Framework
https://github.com/structuralequationmodels/structuralequationmodels.jl
Science Score: 67.0%
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✓CITATION.cff file
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✓DOI references
Found 2 DOI reference(s) in README -
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Links to: zenodo.org -
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○Scientific vocabulary similarity
Low similarity (14.4%) to scientific vocabulary
Keywords
Repository
A fast and flexible Structural Equation Modelling Framework
Basic Info
- Host: GitHub
- Owner: StructuralEquationModels
- License: mit
- Language: Julia
- Default Branch: main
- Homepage: https://structuralequationmodels.github.io/StructuralEquationModels.jl/dev/
- Size: 3.66 MB
Statistics
- Stars: 50
- Watchers: 1
- Forks: 6
- Open Issues: 36
- Releases: 7
Topics
Metadata Files
README.md
StructuralEquationModels.jl
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[!NOTE]
Check out our preprint on the package!
What is this Package for?
This is a package for Structural Equation Modeling. It is still in development. Models you can fit include - Linear SEM that can be specified in RAM (or LISREL) notation - ML, GLS and FIML estimation - Regularized SEM (Ridge, Lasso, L0, ...) - Multigroup SEM - Sums of arbitrary loss functions (everything the optimizer can handle).
What are the merits?
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:
- you want to extend SEM (e.g. add a new objective function) and need an extensible framework
- you want to extend SEM, and your implementation needs to be fast (because you want to do a simulation, for example)
- you want to fit the same model(s) to many datasets (bootstrapping, simulation studies)
- you are planning a study and would like to do power simulations
The package makes use of - Symbolics.jl for symbolically precomputing parts of the objective and gradients to generate fast, specialized functions. - SparseArrays.jl to speed up symbolic computations. - Optim.jl and NLopt.jl to provide a range of different Optimizers/Linesearches. - ProximalAlgorithms.jl for regularization. - FiniteDiff.jl and to provide gradient approximations for user-defined loss functions.
At the moment, we are still working on:
- optimizing performance for big models (with hundreds of parameters)
Questions?
If you have questions you may ask them here in the issues. Please observe our code of conduct.
Owner
- Name: StructuralEquationModels
- Login: StructuralEquationModels
- Kind: organization
- Repositories: 4
- Profile: https://github.com/StructuralEquationModels
Citation (CITATION.cff)
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: StructuralEquationModels.jl
message: >-
Please cite StructuralEquationModels.jl if you use
it for your research.
type: software
authors:
- family-names: Ernst
given-names: Maximilian Stefan
email: ernst@mpib-berlin.mpg.de
affiliation: Max Planck Institute for Human Development
orcid: 'https://orcid.org/0000-0003-2237-6255'
- given-names: Aaron
family-names: Peikert
email: peikert@mpib-berlin.mpg.de
affiliation: Max Planck Institute for Human Development
orcid: 'https://orcid.org/0000-0001-7813-818X'
repository-code: >-
https://github.com/StructuralEquationModels/StructuralEquationModels.jl
license: MIT
doi: 10.5281/zenodo.6719626
GitHub Events
Total
- Create event: 23
- Release event: 3
- Issues event: 53
- Watch event: 5
- Delete event: 2
- Issue comment event: 71
- Push event: 77
- Pull request review event: 53
- Pull request review comment event: 49
- Pull request event: 59
Last Year
- Create event: 23
- Release event: 3
- Issues event: 53
- Watch event: 5
- Delete event: 2
- Issue comment event: 71
- Push event: 77
- Pull request review event: 53
- Pull request review comment event: 49
- Pull request event: 59
Committers
Last synced: almost 3 years ago
All Time
- Total Commits: 740
- Total Committers: 4
- Avg Commits per committer: 185.0
- Development Distribution Score (DDS): 0.082
Top Committers
| Name | Commits | |
|---|---|---|
| maximilian | m****t@g****m | 679 |
| Aaron Peikert | a****t@p****e | 35 |
| Maximilian-Stefan-Ernst | 3****t@u****m | 25 |
| nickhaf | 8****f@u****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 117
- Total pull requests: 120
- Average time to close issues: 9 months
- Average time to close pull requests: 15 days
- Total issue authors: 11
- Total pull request authors: 7
- Average comments per issue: 0.8
- Average comments per pull request: 1.08
- Merged pull requests: 93
- Bot issues: 0
- Bot pull requests: 9
Past Year
- Issues: 18
- Pull requests: 46
- Average time to close issues: about 2 months
- Average time to close pull requests: 3 days
- Issue authors: 5
- Pull request authors: 4
- Average comments per issue: 1.0
- Average comments per pull request: 0.63
- Merged pull requests: 36
- Bot issues: 0
- Bot pull requests: 3
Top Authors
Issue Authors
- Maximilian-Stefan-Ernst (89)
- aaronpeikert (11)
- nickhaf (6)
- brandmaier (3)
- alyst (3)
- anggoran (1)
- gdalle (1)
- dsryu0822 (1)
- dependabot[bot] (1)
- veroyatnost (1)
- JuliaTagBot (1)
- moritzketzer (1)
Pull Request Authors
- Maximilian-Stefan-Ernst (89)
- alyst (30)
- dependabot[bot] (15)
- aaronpeikert (14)
- brandmaier (2)
- LeonieHagitte (1)
- nickhaf (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
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Total downloads:
- julia 6 total
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 10
juliahub.com: StructuralEquationModels
A fast and flexible Structural Equation Modelling Framework
- Homepage: https://structuralequationmodels.github.io/StructuralEquationModels.jl/dev/
- Documentation: https://docs.juliahub.com/General/StructuralEquationModels/stable/
- License: MIT
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Latest release: 0.4.2
published 11 months ago
Rankings
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