hardhat: Construct Modeling Packages
Building modeling packages is hard. A large amount of effort generally goes into providing an implementation for a new method that is efficient, fast, and correct, but often less emphasis is put on the user interface. A good interface requires specialized knowledge about S3 methods and formulas, which the average package developer might not have. The goal of 'hardhat' is to reduce the burden around building new modeling packages by providing functionality for preprocessing, predicting, and validating input.
| Version: | 1.4.0 |
| Depends: | R (≥ 3.5.0) |
| Imports: | cli (≥ 3.6.0), glue (≥ 1.6.2), rlang (≥ 1.1.0), tibble (≥ 3.2.1), vctrs (≥ 0.6.0) |
| Suggests: | covr, crayon, devtools, knitr, Matrix, modeldata (≥ 0.0.2), recipes (≥ 1.0.5), rmarkdown (≥ 2.3), roxygen2, testthat (≥ 3.0.0), usethis (≥ 2.1.5), withr (≥ 3.0.0) |
| Published: | 2024-06-02 |
| DOI: | 10.32614/CRAN.package.hardhat |
| Author: | Hannah Frick 
[aut, cre],
Davis Vaughan [aut],
Max Kuhn [aut],
Posit Software, PBC [cph, fnd] |
| Maintainer: | Hannah Frick <hannah at posit.co> |
| BugReports: | https://github.com/tidymodels/hardhat/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/tidymodels/hardhat, https://hardhat.tidymodels.org |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | hardhat results |
Documentation:
| Reference manual: | hardhat.pdf |
| Vignettes: |
Forging data for predictions Molding data for modeling Creating Modeling Packages With hardhat |
Downloads:
| Package source: | hardhat_1.4.0.tar.gz |
| Windows binaries: | r-devel: hardhat_1.4.0.zip, r-release: hardhat_1.4.0.zip, r-oldrel: hardhat_1.4.0.zip |
| macOS binaries: | r-release (arm64): hardhat_1.4.0.tgz, r-oldrel (arm64): hardhat_1.4.0.tgz, r-release (x86_64): hardhat_1.4.0.tgz, r-oldrel (x86_64): hardhat_1.4.0.tgz |
| Old sources: | hardhat archive |
Reverse dependencies:
| Reverse imports: | agua, applicable, baguette, brulee, censored, cuda.ml, dann, dials, healthyR.ts, lnmixsurv, modeltime, modeltime.resample, parsnip, probably, recipes, tabnet, themis, tidyclust, tidycmprsk, tidymodels, tune, vetiver, viralmodels, waywiser, workflows, workflowsets, yardstick |
| Reverse suggests: | autostats, embed, healthyR.ai, mmrm, nestedmodels, orbital, textrecipes |
Linking:
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