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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 |
Reference manual: | SAMGEP.pdf |
Vignettes: |
Simulated Example |
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 |
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.