ELMSurv: Extreme Learning Machine for Survival Analysis

We use the Buckley-James method to impute the data and extend the emerging Extreme Learning Machine approach to survival analysis. Currently, only right censored data are supported. For a detailed information, see the paper by Hong Wang, Jianxin Wang and Lifeng Zhou (2017) <https://github.com/whcsu/ELMSurv/blob/master/elmsurv-revised.pdf>, which will appear in Applied Intelligence <https://link.springer.com/journal/10489> soon.

Version: 0.4
Imports: Rcpp (≥ 0.12.4), survival
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown
Published: 2017-09-03
Author: Hong Wang
Maintainer: Hong Wang <wh at csu.edu.cn>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/whcsu/ELMSurv
NeedsCompilation: yes
CRAN checks: ELMSurv results


Reference manual: ELMSurv.pdf
Vignettes: Vignette Title
Package source: ELMSurv_0.4.tar.gz
Windows binaries: r-devel: ELMSurv_0.4.zip, r-release: ELMSurv_0.4.zip, r-oldrel: ELMSurv_0.4.zip
OS X El Capitan binaries: r-release: ELMSurv_0.4.tgz
OS X Mavericks binaries: r-oldrel: ELMSurv_0.4.tgz


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