Package: rrscale 1.0
rrscale: Robust Re-Scaling to Better Recover Latent Effects in Data
Non-linear transformations of data to better discover latent effects. Applies a sequence of three transformations (1) a Gaussianizing transformation, (2) a Z-score transformation, and (3) an outlier removal transformation. A publication describing the method has the following citation: Gregory J. Hunt, Mark A. Dane, James E. Korkola, Laura M. Heiser & Johann A. Gagnon-Bartsch (2020) "Automatic Transformation and Integration to Improve Visualization and Discovery of Latent Effects in Imaging Data", Journal of Computational and Graphical Statistics, <doi:10.1080/10618600.2020.1741379>.
Authors:
rrscale_1.0.tar.gz
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rrscale_1.0.tgz(r-4.4-any)rrscale_1.0.tgz(r-4.3-any)
rrscale_1.0.tar.gz(r-4.5-noble)rrscale_1.0.tar.gz(r-4.4-noble)
rrscale_1.0.tgz(r-4.4-emscripten)rrscale_1.0.tgz(r-4.3-emscripten)
rrscale.pdf |rrscale.html✨
rrscale/json (API)
| # Install 'rrscale' in R: |
| install.packages('rrscale', repos = c('https://gjhunt.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 4 years agofrom:fa68683194. Checks:OK: 1 NOTE: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 09 2024 |
| R-4.5-win | NOTE | Nov 09 2024 |
| R-4.5-linux | NOTE | Nov 09 2024 |
| R-4.4-win | NOTE | Nov 09 2024 |
| R-4.4-mac | NOTE | Nov 09 2024 |
| R-4.3-win | NOTE | Nov 09 2024 |
| R-4.3-mac | NOTE | Nov 09 2024 |
Exports:asinhbox_coxbox_cox_expbox_cox_negativebox_cox_plus1box_cox_plusminbox_cox_shiftcentergm_meanlist_transformationslog_box_coxpowerrrscalesvdcwinsor
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Arc-hyperbolic-sine transformation | asinh |
| Traditional box-cox power transformation. Accepts one real parameter | box_cox |
| Exponential of the tranditional box-cox transformation | box_cox_exp |
| A generalized box-cox transformation that can handle negative data | box_cox_negative |
| Box-cox transformation with a shift of 1 added to the data | box_cox_plus1 |
| Box-cox transformation with the data shifted so that it is positive | box_cox_plusmin |
| Box-cox transformation of shifted variable | box_cox_shift |
| Centers the data column-wise | center |
| Calculate the geometric mean | gm_mean |
| List possible transformations | list_transformations |
| Log of the traditional box-cox transformation | log_box_cox |
| Simple power transformation | power |
| Re-scale a data matrix | rrscale |
| The completed SVD | svdc |
| Winsorizes the data | winsor |
