Package: cmenet 0.1.2
Simon Mak
cmenet: Bi-Level Selection of Conditional Main Effects
Provides functions for implementing cmenet - a bi-level variable selection method for conditional main effects (see Mak and Wu (2018) <doi:10.1080/01621459.2018.1448828>). CMEs are reparametrized interaction effects which capture the conditional impact of a factor at a fixed level of another factor. Compared to traditional two-factor interactions, CMEs can quantify more interpretable interaction effects in many problems. The current implementation performs variable selection on only binary CMEs; we are working on an extension for the continuous setting.
Authors:
cmenet_0.1.2.tar.gz
cmenet_0.1.2.tar.gz(r-4.5-noble)cmenet_0.1.2.tar.gz(r-4.4-noble)
cmenet_0.1.2.tgz(r-4.4-emscripten)cmenet_0.1.2.tgz(r-4.3-emscripten)
cmenet.pdf |cmenet.html✨
cmenet/json (API)
| # Install 'cmenet' in R: |
| install.packages('cmenet', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- maize - Maize dataset
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:78b54099c4. Checks:OK: 1 NOTE: 1. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 04 2024 |
| R-4.5-linux-x86_64 | NOTE | Dec 04 2024 |
Exports:cmenetcv.cmenetfull.model.mtxpredictcme
Dependencies:codetoolsforeachglmnethierNetiteratorslatticeMASSMatrixRcppRcppArmadilloRcppEigenshapesparsenetsurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Bi-level selection of conditional main effects (fixed parameters) | cmenet |
| Bi-level selection of conditional main effects | cv.cmenet |
| Generate full model matrix for MEs and CMEs | full.model.mtx |
| Maize dataset | maize |
| Predict using a fitted 'cmenet' object | predictcme |