BAYESDEF: Bayesian Analysis of DSD

Definitive Screening Designs are a class of experimental designs that under factor sparsity have the potential to estimate linear, quadratic and interaction effects with little experimental effort. BAYESDEF is a package that performs a five step strategy to analyze this kind of experiments that makes use of tools coming from the Bayesian approach. It also includes the least absolute shrinkage and selection operator (lasso) as a check (Aguirre VM. (2016) <doi:10.1002/asmb.2160>).

Version: 0.1.0
Depends: R (≥ 3.0.0), tcltk, gWidgets
Imports: readxl, glmnet, REdaS
Published: 2017-06-06
Author: Victor Manuel Aguirre-Torres, Nery Sofia Huerta-Pacheco, Edgar A. Lopez
Maintainer: Nery Sofia Huerta-Pacheco <nehuerta at uv.mx>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://www.uv.mx/personal/nehuerta/bayesdef/
NeedsCompilation: no
SystemRequirements: Tcl/Tk package
CRAN checks: BAYESDEF results

Downloads:

Reference manual: BAYESDEF.pdf
Package source: BAYESDEF_0.1.0.tar.gz
Windows binaries: r-devel: BAYESDEF_0.1.0.zip, r-release: BAYESDEF_0.1.0.zip, r-oldrel: BAYESDEF_0.1.0.zip
OS X El Capitan binaries: r-release: BAYESDEF_0.1.0.tgz
OS X Mavericks binaries: r-oldrel: BAYESDEF_0.1.0.tgz

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