Package: tramicp 0.0-3

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:10.48550/arXiv.2309.12833>).

Authors:Lucas Kook [aut, cre], Sorawit Saengkyongam [ctb], Anton Rask Lundborg [ctb], Torsten Hothorn [ctb], Jonas Peters [ctb]

tramicp_0.0-3.tar.gz
tramicp_0.0-3.zip(r-4.5)tramicp_0.0-3.zip(r-4.4)
tramicp_0.0-3.tgz(r-4.4-any)
tramicp_0.0-3.tar.gz(r-4.5-noble)tramicp_0.0-3.tar.gz(r-4.4-noble)
tramicp_0.0-3.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'))

Peer review:

Bug tracker:https://github.com/lucaskook/tramicp/issues

On CRAN:

4.18 score 6 stars 132 downloads 22 exports 34 dependencies

Last updated 4 months agofrom:ef4567fd6e. Checks:OK: 5. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 30 2024
R-4.5-winOKOct 30 2024
R-4.5-linuxOKOct 30 2024
R-4.4-winOKOct 30 2024
R-4.4-macOKOct 30 2024

Exports:bootstrap_stabilityBoxCoxICPColrICPcotramICPcoxphICPCoxphICPdgp_dicpdicpdicp_controlsglmICPinvariant_setsLehmannICPlmICPLmICPpolrICPPolrICPpvaluesqrfICPrangerICPsurvforestICPsurvregICPSurvregICP

Dependencies:alabamabasefunBBcodetoolscoinconeprojcotramdHSICFormulalatticelibcoinMASSMatrixmatrixStatsmltmodeltoolsmultcompmvtnormnloptrnumDerivorthopolynompolynomqrngquadprograngerRcppRcppArmadilloRcppEigensandwichsurvivalTH.datatramvariableszoo

Readme and manuals

Help Manual

Help pageTopics
Bootstrap stability for TRAMICPbootstrap_stability
Simple data-generating process for illustrating tramicpdgp_dicp
Model-based causal feature selection for general response typesdicp
TRAMICP Controlsdicp_controls
Aliases for implemented model classesBoxCoxICP ColrICP cotramICP CoxphICP coxphICP glmICP implemented_model_classes LehmannICP LmICP lmICP PolrICP polrICP qrfICP rangerICP survforestICP SurvregICP survregICP
Return invariant setsinvariant_sets
Extract set and predictor p-values from tramicp outputspvalues