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sensitivity  

Global Sensitivity Analysis of Model Outputs and Importance Measures
View on CRAN: Click here


Download and install sensitivity package within the R console
Install from CRAN:
install.packages("sensitivity")

Install from Github:
library("remotes")
install_github("cran/sensitivity")

Install by package version:
library("remotes")
install_version("sensitivity", "1.30.1")



Attach the package and use:
library("sensitivity")
Maintained by
Bertrand Iooss
[Scholar Profile | Author Map]
First Published: 2006-06-30
Latest Update: 2023-08-31
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.
How to cite:
Bertrand Iooss (2006). sensitivity: Global Sensitivity Analysis of Model Outputs and Importance Measures. R package version 1.30.1, https://cran.r-project.org/web/packages/sensitivity. Accessed 31 Mar. 2025.
Previous versions and publish date:
1.0 (2006-06-30 10:04), 1.1 (2006-08-03 18:21), 1.2 (2006-08-30 11:19), 1.3-0 (2007-01-05 14:20), 1.3-1 (2008-07-11 18:57), 1.4-0 (2008-07-15 15:47), 1.4-1 (2012-07-01 19:42), 1.5 (2012-09-09 19:06), 1.6-1 (2012-12-28 16:23), 1.6 (2012-11-14 08:10), 1.7 (2013-12-15 13:08), 1.8-0 (2014-02-27 11:49), 1.8-1 (2014-03-04 09:23), 1.8-2 (2014-04-29 07:59), 1.9 (2014-08-26 09:25), 1.10.1 (2014-12-03 09:23), 1.10 (2014-11-26 14:56), 1.11.1 (2015-06-12 13:20), 1.11 (2015-03-06 17:47), 1.12.1 (2016-05-10 06:56), 1.12.2 (2016-06-28 23:40), 1.12 (2016-05-01 18:32), 1.13.0 (2016-12-13 07:57), 1.14.0 (2017-02-11 00:12), 1.15.0 (2017-09-23 23:58), 1.15.1 (2018-07-28 17:00), 1.15.2 (2018-09-02 17:20), 1.16.0 (2019-05-26 00:50), 1.16.1 (2019-06-30 13:50), 1.16.2 (2019-10-09 19:50), 1.16.3 (2019-12-05 19:40), 1.17.0 (2019-12-20 07:30), 1.17.1 (2020-02-14 08:40), 1.18.0 (2020-03-13 10:40), 1.18.1 (2020-04-07 17:40), 1.19.0 (2020-04-29 16:10), 1.20.0 (2020-05-18 18:40), 1.21.0 (2020-06-02 14:10), 1.22.0 (2020-07-18 18:40), 1.22.1 (2020-08-07 07:20), 1.22.2 (2020-10-25 18:00), 1.23.0 (2020-11-28 06:20), 1.23.1 (2020-12-08 19:00), 1.24.0 (2021-01-11 20:10), 1.25.0 (2021-03-20 21:40), 1.26.0 (2021-07-09 11:50), 1.26.1 (2021-09-03 02:10), 1.27.0 (2021-10-20 15:20), 1.27.1 (2022-08-09 10:30), 1.28.0 (2022-09-29 12:30), 1.28.1 (2023-03-19 20:10), 1.29.0 (2023-08-31 12:10), 1.30.0 (2024-01-21 21:10)
Other packages that cited sensitivity R package
View sensitivity citation profile
Other R packages that sensitivity depends, imports, suggests or enhances
Complete documentation for sensitivity
Functions, R codes and Examples using the sensitivity R package
Some associated functions: EPtest . PLI . PLIquantile . PLIquantile_multivar . PLIsuperquantile . PLIsuperquantile_multivar . PoincareChaosSqCoef . PoincareConstant . PoincareOptimal . addelman_const . correlRatio . decoupling . delsa . discrepancyCriteria_cplus . fast99 . johnson . johnsonshap . lmg . maximin_cplus . morris . morrisMultOut . parameterSets . pcc . plot.support . pme . pmvd . qosa . sb . sensiFdiv . sensiHSIC . sensitivity-package . shapleyBlockEstimation . shapleyLinearGaussian . shapleyPermEx . shapleyPermRand . shapleySubsetMc . shapleysobol_knn . sobol . sobol2002 . sobol2007 . sobolEff . sobolGP . sobolMultOut . sobolSalt . sobolSmthSpl . sobolTIIlo . sobolTIIpf . soboljansen . sobolmara . sobolmartinez . sobolowen . sobolrank . sobolrec . sobolrep . sobolroalhs . sobolroauc . sobolshap_knn . soboltouati . squaredIntEstim . src . support . template_replace . testHSIC . testmodels . truncateddistrib . weightTSA . 
Some associated R codes: EPtest.R . PLI.R . PoincareChaosSqCoef.R . PoincareConstant.R . PoincareOptimal.R . RcppExports.R . addelman_kempthorne.R . base.R . bootstats.R . correlRatio.R . delsa.R . discrepancyCriteria_cplus.R . fast99.R . johnson.R . johnsonshap.R . lmg.R . maximin_cplus.R . morris.R . morrisMultOut.R . morris_oat.R . morris_sfd.R . nodeggplot.R . nodeplot.R . parameterSets.R . pcc.R . pme.R . pmvd.R . qosa.R . sb.R . sensiFdiv.R . sensiHSIC.R . shapleyBlockEstimation.R . shapleyLinearGaussian.R . shapleyPermEx.R . shapleyPermRand.R . shapleySubsetMc.R . shapleysobol_knn.R . simplex.R . sobol.R . sobol2002.R . sobol2007.R . sobolEff.R . sobolGP.R . sobolMultOut.R . sobolSalt.R . sobolSmthSpl.R . sobolTIIlo.R . sobolTIIpf.R . soboljansen.R . sobolmara.R . sobolmartinez.R . sobolowen.R . sobolrank.R . sobolrec.R . sobolrep.R . sobolroa_subroutines.R . sobolroalhs.R . sobolroauc.R . sobolshap_knn.R . soboltouati.R . squaredIntEstim.R . src.R . support.R . template_replace.R . testHSIC.R . testmodels.R . weightTSA.R .  Full sensitivity package functions and examples
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