Package: ivitr 0.1.0
Bo Zhang
ivitr: Estimate IV-Optimal Individualized Treatment Rules
A method that estimates an IV-optimal individualized treatment rule. An individualized treatment rule is said to be IV-optimal if it minimizes the maximum risk with respect to the putative IV and the set of IV identification assumptions. Please refer to <arxiv:2002.02579> for more details on the methodology and some theory underpinning the method. Function IV-PILE() uses functions in the package 'locClass'. Package 'locClass' can be accessed and installed from the 'R-Forge' repository via the following link: <https://r-forge.r-project.org/projects/locclass/>. Alternatively, one can install the package by entering the following in R: 'install.packages("locClass", repos="<http://R-Forge.R-project.org>")'.
Authors:
ivitr_0.1.0.tar.gz
ivitr_0.1.0.tar.gz(r-4.5-noble)ivitr_0.1.0.tar.gz(r-4.4-noble)
ivitr_0.1.0.tgz(r-4.4-emscripten)ivitr_0.1.0.tgz(r-4.3-emscripten)
ivitr.pdf |ivitr.html✨
ivitr/json (API)
| # Install 'ivitr' in R: |
| install.packages('ivitr', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- dt_Rouse - Rouse (1995) dataset
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 4 years agofrom:4404053c31. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 27 2024 |
| R-4.5-linux | OK | Oct 27 2024 |
Exports:estimate_BP_boundestimate_Sid_boundIV_PILE
Dependencies:clidplyrfansigenericsgluelifecyclemagrittrnnetpillarpkgconfigR6randomForestrlangtibbletidyselectutf8vctrswithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Rouse (1995) dataset | dt_Rouse |
| Estimate the Balke-Pearl bound for each instance in a dataset | estimate_BP_bound |
| Estimate the partial identification bound as in Siddique (2013, JASA) for each instance in a dataset | estimate_Sid_bound |
| Estimate an IV-optimal individualized treatment rule | IV_PILE |