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Statisticians often want to compare the fit of different models on the same data set. However, this usually involves a lot of manual code to fish items out of summary() or plain model objects. 'modelfactory' offers the capability to pass multiple models in and get out metrics or coefficients for quick comparison with easy-to-remember syntax.
| Version: | 1.0.0 |
| Imports: | dplyr, MASS, stats, tibble |
| Suggests: | testthat (≥ 3.0.0), lme4 |
| Published: | 2024-01-31 |
| DOI: | 10.32614/CRAN.package.modelfactory |
| Author: | Will Tirone [aut, cre, cph] |
| Maintainer: | Will Tirone <will.tirone1 at gmail.com> |
| BugReports: | https://github.com/WillTirone/modelfactory/issues |
| License: | MIT + file LICENSE |
| URL: | https://willtirone.github.io/modelfactory/, https://github.com/WillTirone/modelfactory |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | modelfactory results |
| Reference manual: | modelfactory.pdf |
| Package source: | modelfactory_1.0.0.tar.gz |
| Windows binaries: | r-devel: modelfactory_1.0.0.zip, r-release: modelfactory_1.0.0.zip, r-oldrel: modelfactory_1.0.0.zip |
| macOS binaries: | r-release (arm64): modelfactory_1.0.0.tgz, r-oldrel (arm64): modelfactory_1.0.0.tgz, r-release (x86_64): modelfactory_1.0.0.tgz, r-oldrel (x86_64): modelfactory_1.0.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.