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.
- Version0.1.0
- R version≥ 2.10
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Last release06/01/2022
Documentation
Team
Justin Thorp
Luo Li
Show author detailsRolesAuthorJuanjuan Fan
Show author detailsRolesAuthor
Insights
Last 30 days
This package has been downloaded 166 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 7 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 1,932 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Jan 22, 2025 with 27 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports6 packages
- Linking To2 packages