Package: tramicp 0.1-0
tramicp: Model-Based Causal Feature Selection for General Response Types
Extends invariant causal prediction (Peters et al., 2016, <doi:10.1111/rssb.12167>) to generalized linear and transformation models (Hothorn et al., 2018, <doi:10.1111/sjos.12291>). The methodology is described in Kook et al. (2023, <doi:10.1080/01621459.2024.2395588>).
Authors:
tramicp_0.1-0.tar.gz
tramicp_0.1-0.zip(r-4.5)tramicp_0.1-0.zip(r-4.4)
tramicp_0.1-0.tgz(r-4.5-any)tramicp_0.1-0.tgz(r-4.4-any)
tramicp_0.1-0.tar.gz(r-4.5-noble)tramicp_0.1-0.tar.gz(r-4.4-noble)
tramicp_0.1-0.tgz(r-4.4-emscripten)
tramicp.pdf |tramicp.html✨
tramicp/json (API)
| # Install 'tramicp' in R: |
| install.packages('tramicp', repos = c('https://lucaskook.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/lucaskook/tramicp/issues
Last updated 1 months agofrom:aa01c285af. Checks:6 OK. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 02 2025 |
| R-4.5-win | OK | Mar 02 2025 |
| R-4.5-mac | OK | Mar 02 2025 |
| R-4.5-linux | OK | Mar 02 2025 |
| R-4.4-win | OK | Mar 02 2025 |
| R-4.4-mac | OK | Mar 02 2025 |
Exports:bootstrap_stabilityBoxCoxICPColrICPcotramICPcoxphICPCoxphICPdgp_dicpdicpdicp_controlsglmICPinvariant_setsLehmannICPlmICPLmICPpolrICPPolrICPpvaluesqrfICPrangerICPsurvforestICPsurvregICPSurvregICP
Dependencies:alabamabasefunBBcodetoolscoinconeprojcotramdHSICFormulalatticelibcoinMASSMatrixmatrixStatsmltmodeltoolsmultcompmvtnormnloptrnumDerivorthopolynompolynomqrngquadprograngerRcppRcppArmadilloRcppEigensandwichsurvivalTH.datatramvariableszoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Bootstrap stability for TRAMICP | bootstrap_stability |
| Simple data-generating process for illustrating tramicp | dgp_dicp |
| Model-based causal feature selection for general response types | dicp |
| TRAMICP Controls | dicp_controls |
| Aliases for implemented model classes | BoxCoxICP ColrICP cotramICP CoxphICP coxphICP glmICP implemented_model_classes LehmannICP LmICP lmICP PolrICP polrICP qrfICP rangerICP survforestICP SurvregICP survregICP |
| Return invariant sets | invariant_sets |
| Extract set and predictor p-values from tramicp outputs | pvalues |
