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>.

Version: 0.1.0
Imports: Matrix, survival, pracma, foreach, doParallel, parallel, Rcpp
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown
Published: 2020-11-12
Author: Yuri Ahuja [aut, cre]
Maintainer: Yuri Ahuja <Yuri_Ahuja at hms.harvard.edu>
BugReports: https://github.com/celehs/SCORNET/issues
License: GPL-3
URL: https://github.com/celehs/SCORNET
NeedsCompilation: yes
Materials: README
CRAN checks: SCORNET results

Downloads:

Reference manual: SCORNET.pdf
Vignettes: Simulated Example
Package source: SCORNET_0.1.0.tar.gz
Windows binaries: r-devel: SCORNET_0.1.0.zip, r-release: SCORNET_0.1.0.zip, r-oldrel: SCORNET_0.1.0.zip
macOS binaries: r-release: SCORNET_0.1.0.tgz, r-oldrel: SCORNET_0.1.0.tgz

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