Package: svyVarSel 1.0.1
svyVarSel: Variable Selection for Complex Survey Data
Fit design-based linear and logistic elastic nets with complex survey data considering the sampling design when defining training and test sets using replicate weights. Methods implemented in this package are described in: A. Iparragirre, T. Lumley, I. Barrio, I. Arostegui (2024) <doi:10.1002/sta4.578>.
Authors:
svyVarSel_1.0.1.tar.gz
svyVarSel_1.0.1.zip(r-4.5)svyVarSel_1.0.1.zip(r-4.4)svyVarSel_1.0.1.zip(r-4.3)
svyVarSel_1.0.1.tgz(r-4.4-any)svyVarSel_1.0.1.tgz(r-4.3-any)
svyVarSel_1.0.1.tar.gz(r-4.5-noble)svyVarSel_1.0.1.tar.gz(r-4.4-noble)
svyVarSel_1.0.1.tgz(r-4.4-emscripten)svyVarSel_1.0.1.tgz(r-4.3-emscripten)
svyVarSel.pdf |svyVarSel.html✨
svyVarSel/json (API)
NEWS
| # Install 'svyVarSel' in R: |
| install.packages('svyVarSel', repos = c('https://aiparragirre.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/aiparragirre/svyvarsel/issues
- simdata_lasso_binomial - Simulated complex survey data
complex-survey-dataelastic-netslassoreplicate-weightsvariable-selection
Last updated 7 days agofrom:ee8240efb8. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 17 2024 |
| R-4.5-win | OK | Oct 17 2024 |
| R-4.5-linux | OK | Oct 17 2024 |
| R-4.4-win | OK | Oct 17 2024 |
| R-4.4-mac | OK | Oct 17 2024 |
| R-4.3-win | OK | Oct 17 2024 |
| R-4.3-mac | OK | Oct 17 2024 |
Exports:replicate.weightswelnetwelnet.plotwlassowlasso.plot
Dependencies:codetoolsDBIforeachglmnetiteratorslatticeMatrixminqamitoolsnumDerivRcppRcppArmadilloRcppEigenshapesurveysurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Replicate weights | replicate.weights |
| Simulated complex survey data | simdata_lasso_binomial |
| Weighted (linear or logistic) elastic-nets for complex survey data | welnet |
| Plot welnet object | welnet.plot |
| Weighted LASSO prediction models for complex survey data | wlasso |
| Plot weighted LASSO object | wlasso.plot |
