Package: activegp 1.1.1

Nathan Wycoff

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. (JCGS, 2021) <doi:10.48550/arXiv.1907.11572>.

Authors:Nathan Wycoff, Mickael Binois

activegp_1.1.1.tar.gz
activegp_1.1.1.tar.gz(r-4.5-noble)activegp_1.1.1.tar.gz(r-4.4-noble)
activegp_1.1.1.tgz(r-4.4-emscripten)activegp_1.1.1.tgz(r-4.3-emscripten)
activegp.pdf |activegp.html
activegp/json (API)
NEWS

# Install 'activegp' in R:
install.packages('activegp', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cpp

1.23 score 17 scripts 379 downloads 19 exports 8 dependencies

Last updated 7 months agofrom:df008c45f4. Checks:OK: 1 NOTE: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 22 2024
R-4.5-linux-x86_64NOTEDec 22 2024

Exports:C_GPC_GP_ciC_GP_cppC_QC_trC_varC_var2domain_to_Rdomain_to_unitgrad_est_subspacelogLikHessianLt_GPn11_2_01quick_Csubspace_distupdate_C2W_kappa_ijW_kappa_ij_upW_kappa_lk

Dependencies:DiceDesignhetGPlhsMASSnumDerivRcppRcppArmadilloRcppProgress