Package: dipm 1.9

Cai Li

dipm: Depth Importance in Precision Medicine (DIPM) Method

An implementation by Chen, Li, and Zhang (2022) <doi:10.1093/bioadv/vbac041> of the Depth Importance in Precision Medicine (DIPM) method in Chen and Zhang (2022) <doi:10.1093/biostatistics/kxaa021> and Chen and Zhang (2020) <doi:10.1007/978-3-030-46161-4_16>. The DIPM method is a classification tree that searches for subgroups with especially poor or strong performance in a given treatment group.

Authors:Cai Li [aut, cre], Victoria Chen [aut], Heping Zhang [aut]

dipm_1.9.tar.gz
dipm_1.9.tar.gz(r-4.5-noble)dipm_1.9.tar.gz(r-4.4-noble)
dipm_1.9.tgz(r-4.4-emscripten)dipm_1.9.tgz(r-4.3-emscripten)
dipm.pdf |dipm.html✨
dipm/json (API)

# Install 'dipm' in R:
install.packages('dipm', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openmp– GCC OpenMP (GOMP) support library

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

1.00 score 401 downloads 4 exports 35 dependencies

Last updated 2 years agofrom:23475b35f9. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 21 2024
R-4.5-linux-x86_64OKNov 21 2024

Exports:dipmnode_dipmpmprunespmtree

Dependencies:clicolorspacefansifarverFormulaggplot2gluegtableinumisobandlabelinglatticelibcoinlifecyclemagrittrMASSMatrixmgcvmunsellmvtnormnlmepartykitpillarpkgconfigR6RColorBrewerrlangrpartscalessurvivaltibbleutf8vctrsviridisLitewithr