Package: TPCselect 0.8.3
TPCselect: Variable Selection via Threshold Partial Correlation
A threshold partial correlation approach to selecting important variables in linear models of L. and others (2017) at <doi:10.5705/ss.202015.0473>, and in partial linear models of L. and others (2018) at <doi:10.1016/j.jmva.2018.06.005>. This package also extends the PC-simple algorithm of B. and others (2010) at <doi:10.1093/biomet/asq008> to partial linear models.
Authors:
TPCselect_0.8.3.tar.gz
TPCselect_0.8.3.zip(r-4.5)TPCselect_0.8.3.zip(r-4.4)TPCselect_0.8.3.zip(r-4.3)
TPCselect_0.8.3.tgz(r-4.4-any)TPCselect_0.8.3.tgz(r-4.3-any)
TPCselect_0.8.3.tar.gz(r-4.5-noble)TPCselect_0.8.3.tar.gz(r-4.4-noble)
TPCselect_0.8.3.tgz(r-4.4-emscripten)TPCselect_0.8.3.tgz(r-4.3-emscripten)
TPCselect.pdf |TPCselect.html✨
TPCselect/json (API)
| # Install 'TPCselect' in R: |
| install.packages('TPCselect', repos = c('https://cynyus.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 1 years agofrom:c916540c85. Checks:OK: 1 NOTE: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 01 2024 |
| R-4.5-win | NOTE | Nov 01 2024 |
| R-4.5-linux | NOTE | Nov 01 2024 |
| R-4.4-win | NOTE | Nov 01 2024 |
| R-4.4-mac | NOTE | Nov 01 2024 |
| R-4.3-win | NOTE | Nov 01 2024 |
| R-4.3-mac | NOTE | Nov 01 2024 |
Exports:generate_toy_pldataTPCTPC_BICTPC_plTPC_pl_BICTPCselect
Dependencies:corpcorGPArotationKernSmoothlatticeMASSmnormtnlmepsych
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| A function to generate toy partial linear model data | generate_toy_pldata |
| Variable Selection via Thresholded Partial Correlation | TPC TPCselect |
| Variable Selection via Thresholded Partial Correlation | TPC_BIC |
| Variable Selection via Thresholded Partial Correlation | TPC_pl |
| Variable Selection via Thresholded Partial Correlation | TPC_pl_BIC |
