Package: PLSiMCpp 1.0.4
Shunyao Wu
PLSiMCpp: Methods for Partial Linear Single Index Model
Estimation, hypothesis tests, and variable selection in partially linear single-index models. Please see H. (2010) at <doi:10.1214/10-AOS835> for more details.
Authors:
PLSiMCpp_1.0.4.tar.gz
PLSiMCpp_1.0.4.tar.gz(r-4.5-noble)PLSiMCpp_1.0.4.tar.gz(r-4.4-noble)
PLSiMCpp_1.0.4.tgz(r-4.4-emscripten)PLSiMCpp_1.0.4.tgz(r-4.3-emscripten)
PLSiMCpp.pdf |PLSiMCpp.html✨
PLSiMCpp/json (API)
| # Install 'PLSiMCpp' in R: |
| install.packages('PLSiMCpp', 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 2 years agofrom:bf0a5b7bc3. Checks:OK: 1 NOTE: 1. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 10 2024 |
| R-4.5-linux-x86_64 | NOTE | Dec 10 2024 |
Exports:plsim.bwplsim.estplsim.iniplsim.lamplsim.MAVEplsim.npTestplsim.pTestplsim.vs.hardplsim.vs.soft
Dependencies:clicrayongluelifecyclemagrittrpurrrRcppRcppArmadillorlangvctrs
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| select bandwidth | bwsel_Core bwsel_new.CrossValidation bwsel_new.default deal_formula plsim.bw plsim.bw.default plsim.bw.formula summary.pls |
| Profile Least Squares Estimator | plsim.est plsim.est.default plsim.est.formula |
| Initialize coefficients | plsim.ini plsim.ini.default plsim.ini.formula |
| Select lambda for Penalized Profile Least Squares Estimator | plsim.lam plsim.lam.default plsim.lam.formula |
| Minimum Average Variance Estimation | plsim.MAVE plsim.MAVE.default plsim.MAVE.formula |
| Testing nonparametric component | plsim.npTest |
| Testing Parametric Components | plsim.pTest |
| Variable Selection for Partial Linear Single Index Models | dropOneVar plsim.vs.hard plsim.vs.hard.default plsim.vs.hard.formula stepWise varSelCore varSelCore.PPLSE varSelCore.StepWise |
| Penalized Profile Least Squares Estimator | plsim.vs.soft plsim.vs.soft.default plsim.vs.soft.formula |
| Predict according to the Estimated Parameters | predict.pls |
