GADGET: Gaussian Process Approximations for Designing Experiments

Computes near-optimal Bayesian experimental designs with Gaussian processes optimization following the algorithm presented by B. Weaver, et al. (2016) <doi:10.1214/15-BA945> for either physical or sequential computer experiments.

Version: 0.2.0
Imports: DiceKriging, DiceOptim, lhs, pbapply, utils, graphics, stats
Suggests: testthat, parallel
Published: 2020-01-24
Author: Isaac Michaud [aut, cre], Brian Weaver [aut], Brian Williams [aut]
Maintainer: Isaac Michaud <imichaud at>
License: BSD_3_clause + file LICENSE
Copyright: see file COPYRIGHTS
NeedsCompilation: no
Materials: README NEWS
CRAN checks: GADGET results


Reference manual: GADGET.pdf
Package source: GADGET_0.2.0.tar.gz
Windows binaries: r-prerelease:, r-release:, r-oldrel:
macOS binaries: r-prerelease: GADGET_0.2.0.tgz, r-release: GADGET_0.2.0.tgz, r-oldrel: GADGET_0.2.0.tgz


Please use the canonical form to link to this page.