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Training and validation of a custom (or data-driven) Structural Equation Models using layer-wise Deep Neural Networks or node-wise Machine Learning algorithms, which extend the fitting procedures of the 'SEMgraph' R package <doi:10.32614/CRAN.package.SEMgraph>.
| Version: | 0.1.0 |
| Depends: | SEMgraph (≥ 1.2.2), igraph (≥ 2.0.0), R (≥ 4.0) |
| Imports: | cito, corpcor, lavaan, mgcv, NeuralNetTools, nnet, ranger, shapr, torch, xgboost |
| Published: | 2024-09-16 |
| DOI: | 10.32614/CRAN.package.SEMdeep |
| Author: | Mario Grassi [aut], Barbara Tarantino [aut, cre] |
| Maintainer: | Barbara Tarantino <barbara.tarantino01 at universitadipavia.it> |
| License: | GPL (≥ 3) |
| URL: | https://github.com/BarbaraTarantino/SEMdeep |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | SEMdeep results |
| Reference manual: | SEMdeep.pdf |
| Package source: | SEMdeep_0.1.0.tar.gz |
| Windows binaries: | r-devel: SEMdeep_0.1.0.zip, r-release: SEMdeep_0.1.0.zip, r-oldrel: SEMdeep_0.1.0.zip |
| macOS binaries: | r-release (arm64): SEMdeep_0.1.0.tgz, r-oldrel (arm64): SEMdeep_0.1.0.tgz, r-release (x86_64): SEMdeep_0.1.0.tgz, r-oldrel (x86_64): SEMdeep_0.1.0.tgz |
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