Package: CERFIT 0.1.0

Justin Thorp

CERFIT: Causal Effect Random Forest of Interaction Tress

Fits a Causal Effect Random Forest of Interaction Tress (CERFIT) which is a modification of the Random Forest algorithm where each split is chosen to maximize subgroup treatment heterogeneity. Doing this allows it to estimate the individualized treatment effect for each observation in either randomized controlled trial (RCT) or observational data. For more information see X. Su, A. T. Peña, L. Liu, and R. A. Levine (2018) <doi:10.48550/arXiv.1709.04862>.

Authors:Justin Thorp [aut, cre], Luo Li [aut], Juanjuan Fan [aut]

CERFIT_0.1.0.tar.gz
CERFIT_0.1.0.tar.gz(r-4.5-noble)CERFIT_0.1.0.tar.gz(r-4.4-noble)
CERFIT_0.1.0.tgz(r-4.4-emscripten)CERFIT_0.1.0.tgz(r-4.3-emscripten)
CERFIT.pdf |CERFIT.html✨
CERFIT/json (API)

# Install 'CERFIT' in R:
install.packages('CERFIT', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • educational - Observational Educational Dataset
  • warts - Randomized Controlled Trial Warts Dataset

On CRAN:

Conda-Forge:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascpp

1.70 score 1 scripts 165 downloads 2 exports 67 dependencies

Last updated 3 years agofrom:1d04d96d02. Checks:1 OK, 1 NOTE. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKFeb 25 2025
R-4.5-linux-x86_64NOTEFeb 25 2025

Exports:CERFITMinDepth

Dependencies:backportsCBPSchkclicodetoolscolorspacedata.tableDBIdeldirfansifarverforeachFormulagbmggplot2glmnetgluegtableinterpinumisobanditeratorsjpegjsonlitelabelinglatticelatticeExtralibcoinlifecyclemagrittrMASSMatchItMatrixMatrixModelsmgcvminqamitoolsmunsellmvtnormnlmennetnumDerivpartykitpillarpkgconfigpngR6randomForestRColorBrewerRcppRcppArmadilloRcppEigenRcppProgressrlangrpartscalesshapesurveysurvivaltibbletwangutf8vctrsviridisLitewithrxgboostxtable