Package: lincom 1.2

Yijian Huang

lincom: Linear Biomarker Combination: Empirical Performance Optimization

Perform two linear combination methods for biomarkers: (1) Empirical performance optimization for specificity (or sensitivity) at a controlled sensitivity (or specificity) level of Huang and Sanda (2022) <doi:10.1214/22-aos2210>, and (2) weighted maximum score estimator with empirical minimization of averaged false positive rate and false negative rate. Both adopt the algorithms of Huang and Sanda (2022) <doi:10.1214/22-aos2210>. 'MOSEK' solver is used and needs to be installed; an academic license for 'MOSEK' is free.

Authors:Yijian Huang <[email protected]>

lincom_1.2.tar.gz
lincom_1.2.tar.gz(r-4.5-noble)lincom_1.2.tar.gz(r-4.4-noble)
lincom_1.2.tgz(r-4.4-emscripten)lincom_1.2.tgz(r-4.3-emscripten)
lincom.pdf |lincom.html
lincom/json (API)

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

Peer review:

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

fortran

2.00 score 2 scripts 229 downloads 2 exports 2 dependencies

Last updated 6 months agofrom:61ee036498. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 28 2024
R-4.5-linux-x86_64OKNov 28 2024

Exports:eumwmse

Dependencies:RmosekSparseM

Linear Biomarker Combination: Empirical Performance Optimization

Rendered fromlincom.Rmdusingknitr::rmarkdownon Nov 28 2024.

Last update: 2023-06-21
Started: 2023-06-21