Package: ddsPLS
Version: 1.0.61
Date: 2019-01-21
Title: Data-Driven Sparse PLS Robust to Missing Samples for Mono and
        Multi-Block Data Sets
Description: Allows to build Multi-Data-Driven Sparse PLS models. Multi-blocks with 
    high-dimensional settings are particularly sensible to this.
Authors@R: c(person("Hadrien","Lorenzo", role = c("aut", "cre"),
                     email = "hadrien.lorenzo.2015@gmail.com"),
             person("Jerome","Saracco", role = c("aut"),
                     email = "jerome.saracco@math.u-bordeaux1.fr"),
             person("Rodolphe","Thiebaut", role = c("aut"),
                     email = "rodolphe.thiebaut@u-bordeaux.fr"))
Maintainer: Hadrien Lorenzo <hadrien.lorenzo.2015@gmail.com>
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
ByteCompile: true
RoxygenNote: 6.1.0
Imports:
        RColorBrewer,MASS,graphics,stats,Rdpack,doParallel,foreach,parallel
RdMacros: Rdpack
Suggests: knitr,rmarkdown
Depends: R (>= 2.10)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-01-21 09:38:56 UTC; hl1
Author: Hadrien Lorenzo [aut, cre],
  Jerome Saracco [aut],
  Rodolphe Thiebaut [aut]
Repository: CRAN
Date/Publication: 2019-01-21 10:20:06 UTC
Built: R 3.4.4; ; 2019-04-25 20:42:31 UTC; windows
