The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

SAMGEP: A Semi-Supervised Method for Prediction of Phenotype Event Times

A novel semi-supervised machine learning algorithm to predict phenotype event times using Electronic Health Record (EHR) data.

Version: 0.1.0-1
Depends: R (≥ 3.5.0)
Imports: stats, mvtnorm, nlme, pROC, abind, nloptr, foreach, doParallel, parallel, Rcpp
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown
Published: 2021-01-06
DOI: 10.32614/CRAN.package.SAMGEP
Author: Yuri Ahuja [aut, cre], Tianxi Cai [aut], PARSE LTD [aut]
Maintainer: Yuri Ahuja <Yuri_Ahuja at hms.harvard.edu>
BugReports: https://github.com/celehs/SAMGEP/issues
License: GPL-3
URL: https://github.com/celehs/SAMGEP
NeedsCompilation: yes
Materials: README
CRAN checks: SAMGEP results

Documentation:

Reference manual: SAMGEP.pdf
Vignettes: Simulated Example

Downloads:

Package source: SAMGEP_0.1.0-1.tar.gz
Windows binaries: r-devel: SAMGEP_0.1.0-1.zip, r-release: SAMGEP_0.1.0-1.zip, r-oldrel: SAMGEP_0.1.0-1.zip
macOS binaries: r-release (arm64): SAMGEP_0.1.0-1.tgz, r-oldrel (arm64): SAMGEP_0.1.0-1.tgz, r-release (x86_64): SAMGEP_0.1.0-1.tgz, r-oldrel (x86_64): SAMGEP_0.1.0-1.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=SAMGEP to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.