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Performs goodness of fits tests for both high and low-dimensional linear models. It can test for a variety of model misspecifications including nonlinearity and heteroscedasticity. In addition one can test the significance of potentially large groups of variables, and also produce p-values for the significance of individual variables in high-dimensional linear regression.
| Version: | 0.1.5 |
| Imports: | glmnet, parallel, randomForest, Rcpp, stats |
| LinkingTo: | Rcpp |
| Published: | 2021-07-10 |
| DOI: | 10.32614/CRAN.package.RPtests |
| Author: | Rajen Shah [aut, cre], Peter Buhlmann [aut] |
| Maintainer: | Rajen Shah <r.shah at statslab.cam.ac.uk> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://rss.onlinelibrary.wiley.com/doi/10.1111/rssb.12234 |
| NeedsCompilation: | yes |
| CRAN checks: | RPtests results |
| Reference manual: | RPtests.pdf |
| Package source: | RPtests_0.1.5.tar.gz |
| Windows binaries: | r-devel: RPtests_0.1.5.zip, r-release: RPtests_0.1.5.zip, r-oldrel: RPtests_0.1.5.zip |
| macOS binaries: | r-release (arm64): RPtests_0.1.5.tgz, r-oldrel (arm64): RPtests_0.1.5.tgz, r-release (x86_64): RPtests_0.1.5.tgz, r-oldrel (x86_64): RPtests_0.1.5.tgz |
| Old sources: | RPtests archive |
| Reverse imports: | CondIndTests |
| Reverse suggests: | knockoff |
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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.