Package: CovSel 1.2.1
Jenny Häggström
CovSel: Model-Free Covariate Selection
Model-free selection of covariates under unconfoundedness for situations where the parameter of interest is an average causal effect. This package is based on model-free backward elimination algorithms proposed in de Luna, Waernbaum and Richardson (2011). Marginal co-ordinate hypothesis testing is used in situations where all covariates are continuous while kernel-based smoothing appropriate for mixed data is used otherwise.
Authors:
CovSel_1.2.1.tar.gz
CovSel_1.2.1.tar.gz(r-4.5-noble)CovSel_1.2.1.tar.gz(r-4.4-noble)
CovSel_1.2.1.tgz(r-4.4-emscripten)CovSel_1.2.1.tgz(r-4.3-emscripten)
CovSel.pdf |CovSel.html✨
CovSel/json (API)
| # Install 'CovSel' in R: |
| install.packages('CovSel', repos = c('https://cran.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 9 years agofrom:4a904805bc. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 02 2024 |
| R-4.5-linux | OK | Nov 02 2024 |
Exports:cov.sel
Dependencies:bootcubaturedrlatticeMASSMatrixMatrixModelsnpquadprogquantregRcppSparseMsurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Model-Free Selection of Covariate Sets | cov.sel |
| cov.sel.np | cov.sel.np |
| Simulated Data, Continuous | datc |
| Simulated Data, Factors | datf |
| Simulated Data, Mixed | datfc |
| Real data, Lalonde | lalonde |
| Summary | summary.cov.sel |