ddsPLS

Data-Driven Sparse PLS Robust to Missing Samples for Mono and Multi-Block Data Sets

Allows to build Multi-Data-Driven Sparse PLS models. Multi-blocks with high-dimensional settings are particularly sensible to this.

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Description file content

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.
Maintainer
Hadrien Lorenzo
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

install.packages('ddsPLS')

1.0.61

a day ago

Hadrien Lorenzo

MIT + file LICENSE

Depends on

R (>= 2.10)

Imports

RColorBrewer,MASS,graphics,stats,Rdpack,doParallel,foreach,parallel

Suggests

knitr,rmarkdown

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