activegp: Gaussian Process Based Design and Analysis for the Active Subspace Method

The active subspace method is a sensitivity analysis technique that finds important linear combinations of input variables for a simulator. This package provides functions allowing estimation of the active subspace without gradient information using Gaussian processes as well as sequential experimental design tools to minimize the amount of data required to do so. Implements Wycoff et al. (2019) <arXiv:1907.11572>.

Version: 1.0.5
Depends: R (≥ 3.4.0)
Imports: Rcpp (≥ 0.12.18), hetGP (≥ 1.1.1), lhs, numDeriv, methods
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat
Published: 2020-10-27
Author: Nathan Wycoff, Mickael Binois
Maintainer: Nathan Wycoff <nathw95 at vt.edu>
License: BSD_3_clause + file LICENSE
NeedsCompilation: yes
Materials: NEWS
CRAN checks: activegp results

Downloads:

Reference manual: activegp.pdf
Package source: activegp_1.0.5.tar.gz
Windows binaries: r-devel: activegp_1.0.5.zip, r-release: activegp_1.0.5.zip, r-oldrel: activegp_1.0.5.zip
macOS binaries: r-release: activegp_1.0.5.tgz, r-oldrel: activegp_1.0.5.tgz
Old sources: activegp archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=activegp to link to this page.