Package: ELMSurv
Type: Package
Title: Extreme Learning Machine for Survival Analysis
Version: 0.6
Date: 2019-05-27
Author: Hong Wang
Maintainer: Hong Wang <wh@csu.edu.cn>
Description: First, we use the Buckley-James method to impute the data and extend the emerging extreme learning machine approach to survival analysis. Second, we present a kernel extreme learning machine Cox model regularized by an L_0-based broken adaptive ridge (BAR) penalization method. For a detailed information, see Hong Wang et al(2018) <DOI: 10.1007/s10489-017-1063-4>, Hong Wang and Gang Li(2019) <DOI:10.1002/sim.8090>.
License: GPL (>= 2)
Imports: Rcpp,survival,RcppNumerical,glmnet
LinkingTo: Rcpp,RcppArmadillo,RcppEigen, RcppNumerical
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-05-27 08:23:03 UTC; wh
Repository: CRAN
Date/Publication: 2019-05-27 09:00:17 UTC
