Package: sodavis 1.2
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
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sodavis_1.2.tgz(r-4.4-any)sodavis_1.2.tgz(r-4.3-any)
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sodavis.pdf |sodavis.html✨
sodavis/json (API)
# Install 'sodavis' in R: |
install.packages('sodavis', repos = c('https://yangli88.r-universe.dev', 'https://cloud.r-project.org')) |
- 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
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 7 years agofrom:ca871473e9. Checks:OK: 3 NOTE: 4. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 14 2024 |
R-4.5-win | NOTE | Nov 14 2024 |
R-4.5-linux | NOTE | Nov 14 2024 |
R-4.4-win | NOTE | Nov 14 2024 |
R-4.4-mac | NOTE | Nov 14 2024 |
R-4.3-win | OK | Nov 14 2024 |
R-4.3-mac | OK | Nov 14 2024 |
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 |