Package: ROCSI 0.1.0
Xin Huang
ROCSI: Receiver Operating Characteristic Based Signature Identification
Optimal linear combination predictive signatures for maximizing the area between two Receiver Operating Characteristic (ROC) curves (treatment vs. control).
Authors:
ROCSI_0.1.0.tar.gz
ROCSI_0.1.0.tar.gz(r-4.5-noble)ROCSI_0.1.0.tar.gz(r-4.4-noble)
ROCSI_0.1.0.tgz(r-4.4-emscripten)ROCSI_0.1.0.tgz(r-4.3-emscripten)
ROCSI.pdf |ROCSI.html✨
ROCSI/json (API)
# Install 'ROCSI' in R: |
install.packages('ROCSI', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:eb1d03b580. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 04 2024 |
R-4.5-linux | OK | Dec 04 2024 |
Dependencies:codetoolsforeachglmnetiteratorslatticeMASSMatrixRcppRcppEigenshapesurvival
Readme and manuals
Help Manual
Help page | Topics |
---|---|
AUC | AUC |
beta2theta | beta2theta |
C.index | C.index |
cvfolds0 | cvfolds0 |
data.gen | data.gen |
grad.sub | grad.sub |
gradsqr | gradsqr |
hessAUC | hessAUC |
hessAUC.sub | hessAUC.sub |
HIC | HIC |
MClogit | MClogit |
pair.diff | pair.diff |
pair.diff.surv | pair.diff.surv |
ROCSI | ROCSI |
theta2beta | theta2beta |