Package: sodavis 1.2
Yang Li
sodavis: SODA: Main and Interaction Effects Selection for Logistic Regression, Quadratic Discriminant and General Index Models
Variable and interaction selection are essential to classification in high-dimensional setting. In this package, we provide the implementation of SODA procedure, which is a forward-backward algorithm that selects both main and interaction effects under logistic regression and quadratic discriminant analysis. We also provide an extension, S-SODA, for dealing with the variable selection problem for semi-parametric models with continuous responses.
Authors:
sodavis_1.2.tar.gz
sodavis_1.2.zip(r-4.7-any)sodavis_1.2.zip(r-4.6-any)sodavis_1.2.zip(r-4.5-any)
sodavis_1.2.tgz(r-4.6-any)sodavis_1.2.tgz(r-4.5-any)
sodavis_1.2.tar.gz(r-4.7-any)sodavis_1.2.tar.gz(r-4.6-any)
sodavis_1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
sodavis/json (API)
| # Install 'sodavis' in R: |
| install.packages('sodavis', repos = c('https://cranhaven.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/cranhaven/cranhaven.r-universe.dev/issues
- mich_lung_xx - Gene expression data for Michigan lung cancer study in Beer et al.
- mich_lung_yy - Gene expression data for Michigan lung cancer study in Beer et al.
- pumadyn_isample_x - Pumadyn dataset
- pumadyn_isample_y - Pumadyn dataset
- pumadyn_osample_x - Pumadyn dataset
- pumadyn_osample_y - Pumadyn dataset
Last updated from:ad65fafc47 (on package/sodavis). Checks:7 NOTE, 2 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | NOTE | 95 | ||
| source / vignettes | OK | 164 | ||
| linux-release | NOTE | 94 | ||
| macos-release | NOTE | 113 | ||
| macos-oldrel | NOTE | 101 | ||
| windows-devel | NOTE | 71 | ||
| windows-release | NOTE | 56 | ||
| windows-oldrel | NOTE | 68 | ||
| wasm-release | OK | 90 |
Exports:s_sodas_soda_models_soda_preds_soda_pred_gridsodasoda_trace_CV
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Gene expression data for Michigan lung cancer study in Beer et al. (2002) | mich_lung_xx mich_lung_yy |
| Pumadyn dataset | pumadyn_isample_x pumadyn_isample_y pumadyn_osample_x pumadyn_osample_y |
| S-SODA algorithm for general index model variable selection | s_soda |
| S-SODA model estimation. | s_soda_model |
| Predict the response y using S-SODA model. | s_soda_pred |
| Predict the response y using S-SODA model in a 2-dimensional grid. | s_soda_pred_grid |
| SODA algorithm for variable and interaction selection | soda |
| Calculate a trace of cross-validation error rate for SODA forward-backward procedure | soda_trace_CV |