BNN: Bayesian Neural Network for High-Dimensional Nonlinear Variable Selection

Perform Bayesian variable selection for high-dimensional nonlinear systems and also can be used to test nonlinearity for a general regression problem. The computation can be accelerated using multiple CPUs. You can refer to Liang, F., Li, Q. and Zhou, L. (2017) at <https://www.samsi.info/wp-content/uploads/2016/09/SAMSI_DPDA-Liang.pdf> for detail. The publication "Bayesian Neural Networks for Selection of drug sensitive Genes" will be appear on Journals of American Statistical Association soon.

Version: 1.0.0
Depends: R (≥ 3.0.2)
Published: 2018-01-13
Author: Bochao Jia [aut, cre, cph], Faming Liang [ctb], Robert Gentleman [cph], Ross Ihaka [cph], The R Core Team [cph]
Maintainer: Bochao Jia <jbc409 at ufl.edu>
License: GPL-2
NeedsCompilation: yes
CRAN checks: BNN results

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Reference manual: BNN.pdf
Package source: BNN_1.0.0.tar.gz
Windows binaries: r-devel: BNN_1.0.0.zip, r-release: BNN_1.0.0.zip, r-oldrel: BNN_1.0.0.zip
OS X El Capitan binaries: r-release: BNN_1.0.0.tgz
OS X Mavericks binaries: r-oldrel: not available

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