Package: sensitivity
Version: 1.30.0
Title: Global Sensitivity Analysis of Model Outputs and Importance
        Measures
Author: Bertrand Iooss, Sebastien Da Veiga, Alexandre Janon and Gilles Pujol, with contributions from Baptiste Broto, Khalid Boumhaout, Laura Clouvel, Thibault Delage, Reda El Amri, Jana Fruth, Laurent Gilquin, Joseph Guillaume, Margot Herin, Marouane Il Idrissi, Loic Le Gratiet, Paul Lemaitre, Amandine Marrel, Anouar Meynaoui, Barry L. Nelson, Filippo Monari, Roelof Oomen, Oldrich Rakovec, Bernardo Ramos, Paul Rochet, Olivier Roustant, Gabriel Sarazin, Eunhye Song, Jeremy Staum, Roman Sueur, Taieb Touati, Vanessa Verges, Frank Weber 
Maintainer: Bertrand Iooss <biooss@yahoo.fr>
Depends: R (>= 3.0.0)
Imports: boot, numbers, methods, ggplot2, Rcpp, foreach, dtwclust
LinkingTo: Rcpp, RcppArmadillo
Suggests: condMVNorm, DiceDesign, DiceKriging, doParallel, evd,
        ggExtra, grid, gplots, gtools, igraph, IncDTW, ks, lattice,
        MASS, mc2d, mvtnorm, parallel, plotrix, pracma, proxy,
        randtoolbox, RANN, reshape2, rgl, stringr, triangle, TSP,
        viridisLite, whitening
Description: A collection of functions for sensitivity analysis of model outputs (factor screening, global sensitivity analysis and robustness analysis), for variable importance measures of data, as well as for interpretability of machine learning models. Most of the functions have to be applied on scalar output, but several functions support multi-dimensional outputs.
License: GPL-2
NeedsCompilation: yes
Repository: CRAN
Packaged: 2024-01-20 12:03:03 UTC; F80570
Date/Publication: 2024-01-21 20:10:02 UTC
Built: R 4.2.3; x86_64-w64-mingw32; 2024-04-24 02:37:09 UTC; windows
ExperimentalWindowsRuntime: ucrt
Archs: x64
