Package: SCORNET 0.1.2

Yuri Ahuja

SCORNET: Semi-Supervised Calibration of Risk with Noisy Event Times

A consistent, semi-supervised, non-parametric survival curve estimator optimized for efficient use of Electronic Health Record (EHR) data with a limited number of current status labels. See van der Laan and Robins (1997) <doi:10.2307/2670119>.

Authors:Yuri Ahuja [aut, cre], PARSE Health [aut]

SCORNET_0.1.2.tar.gz
SCORNET_0.1.2.zip(r-4.7)SCORNET_0.1.2.zip(r-4.6)SCORNET_0.1.2.zip(r-4.5)
SCORNET_0.1.2.tgz(r-4.6-x86_64)SCORNET_0.1.2.tgz(r-4.6-arm64)SCORNET_0.1.2.tgz(r-4.5-x86_64)SCORNET_0.1.2.tgz(r-4.5-arm64)
SCORNET_0.1.2.tar.gz(r-4.7-arm64)SCORNET_0.1.2.tar.gz(r-4.7-x86_64)SCORNET_0.1.2.tar.gz(r-4.6-arm64)SCORNET_0.1.2.tar.gz(r-4.6-x86_64)
SCORNET_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
SCORNET/json (API)

# Install 'SCORNET' in R:

install.packages('SCORNET', repos = c('https://celehs.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/celehs/scornet/issues

Pkgdown/docs site:https://celehs.github.io

Uses libs:

c++– GNU Standard C++ Library v3

On CRAN:

cpp

4.48 score 3 stars 3 scripts 159 downloads 1 exports 10 dependencies

Last updated from:fe449012a2. Checks:11 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	NOTE	161
linux-devel-x86_64	NOTE	119
source / vignettes	OK	186
linux-release-arm64	NOTE	118
linux-release-x86_64	NOTE	121
macos-release-arm64	NOTE	131
macos-release-x86_64	NOTE	216
macos-oldrel-arm64	NOTE	122
macos-oldrel-x86_64	NOTE	244
windows-devel	NOTE	153
windows-release	NOTE	148
windows-oldrel	NOTE	162
wasm-release	OK	114