Package: RPtests 0.1.5
RPtests: Goodness of Fit Tests for High-Dimensional Linear Regression Models
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.
Authors:
RPtests_0.1.5.tar.gz
RPtests_0.1.5.zip(r-4.5)RPtests_0.1.5.zip(r-4.4)RPtests_0.1.5.zip(r-4.3)
RPtests_0.1.5.tgz(r-4.4-x86_64)RPtests_0.1.5.tgz(r-4.4-arm64)RPtests_0.1.5.tgz(r-4.3-x86_64)RPtests_0.1.5.tgz(r-4.3-arm64)
RPtests_0.1.5.tar.gz(r-4.5-noble)RPtests_0.1.5.tar.gz(r-4.4-noble)
RPtests_0.1.5.tgz(r-4.4-emscripten)RPtests_0.1.5.tgz(r-4.3-emscripten)
RPtests.pdf |RPtests.html✨
RPtests/json (API)
| # Install 'RPtests' in R: |
| install.packages('RPtests', repos = c('https://rajenshah.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:6296adc362. Checks:OK: 3 NOTE: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 07 2024 |
| R-4.5-win-x86_64 | OK | Nov 07 2024 |
| R-4.5-linux-x86_64 | OK | Nov 07 2024 |
| R-4.4-win-x86_64 | NOTE | Nov 07 2024 |
| R-4.4-mac-x86_64 | NOTE | Nov 07 2024 |
| R-4.4-mac-aarch64 | NOTE | Nov 07 2024 |
| R-4.3-win-x86_64 | NOTE | Nov 07 2024 |
| R-4.3-mac-x86_64 | NOTE | Nov 07 2024 |
| R-4.3-mac-aarch64 | NOTE | Nov 07 2024 |
Exports:pvalRPtestRPtest_singlesparse_projsqrt_lasso
Dependencies:codetoolsforeachglmnetiteratorslatticeMatrixrandomForestRcppRcppEigenshapesurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Compute p-values for 'RPtest' output | pval |
| Goodness of fit tests for potentially high-dimensional linear models | RPtest |
| Test significance of single predictors | RPtest_single |
| Sparse projections using the square-root Lasso | sparse_proj |
| Square-root Lasso regression | sqrt_lasso |
