Package: LSDsensitivity 1.3.0
LSDsensitivity: Sensitivity Analysis Tools for LSD Simulations
Tools for sensitivity analysis of LSD simulation models. Reads object-oriented data produced by LSD simulation models and performs screening and global sensitivity analysis (Sobol decomposition method, Saltelli et al. (2008) ISBN:9780470725177). A Kriging or polynomial meta-model (Kleijnen (2009) <doi:10.1016/j.ejor.2007.10.013>) is estimated using the simulation data to provide the data required by the Sobol decomposition. LSD (Laboratory for Simulation Development) is free software developed by Marco Valente and Marcelo C. Pereira (documentation and downloads available at <https://www.labsimdev.org/>).
Authors:
LSDsensitivity_1.3.0.tar.gz
LSDsensitivity_1.3.0.zip(r-4.5)LSDsensitivity_1.3.0.zip(r-4.4)LSDsensitivity_1.3.0.zip(r-4.3)
LSDsensitivity_1.3.0.tgz(r-4.4-any)LSDsensitivity_1.3.0.tgz(r-4.3-any)
LSDsensitivity_1.3.0.tar.gz(r-4.5-noble)LSDsensitivity_1.3.0.tar.gz(r-4.4-noble)
LSDsensitivity_1.3.0.tgz(r-4.4-emscripten)LSDsensitivity_1.3.0.tgz(r-4.3-emscripten)
LSDsensitivity.pdf |LSDsensitivity.html✨
LSDsensitivity/json (API)
| # Install 'LSDsensitivity' in R: |
| install.packages('LSDsensitivity', repos = c('https://santannaks.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 months agofrom:2fc6aeedda. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 20 2024 |
| R-4.5-win | OK | Nov 20 2024 |
| R-4.5-linux | OK | Nov 20 2024 |
| R-4.4-win | OK | Nov 20 2024 |
| R-4.4-mac | OK | Nov 20 2024 |
| R-4.3-win | OK | Nov 20 2024 |
| R-4.3-mac | OK | Nov 20 2024 |
Exports:elementary.effects.lsdergod.test.lsdkriging.model.lsdmodel.limits.lsdmodel.optim.lsdmodel.pred.lsdpolynomial.model.lsdread.doe.lsdresponse.surface.lsdsobol.decomposition.lsdsymmet.test.lsd
Dependencies:abindbackportsbase64encbootbroombslibcachemcarcarDataclasscliclueclusterclvcodetoolscolorspacecommonmarkcowplotcpp11crayoncurlDerivDiceKrigingdigestdiptestdoBydplyrdtwdtwclustevaluatefansifarverfastmapflexclustfontawesomeforeachforecastFormulafracdifffsgenericsggplot2ggrepelgluegtablehighrhtmltoolshtmlwidgetshttpuvisobanditeratorsjquerylibjsonliteKendallKernSmoothknitrkSampleslabelinglaterlatticelawstatlifecyclelme4lmtestlocpollongitudinalDataLSDinterfacemagrittrMASSMatrixMatrixModelsmemoisemgcvmicrobenchmarkmimeminqamisc3dmodelrmodeltoolsmunsellmvtnormnlmenloptrnnetnumbersnumDerivpbkrtestpdcpillarpkgconfigplyrpromisesproxypurrrquadprogquantmodquantregR6randtoolboxrappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRcppParallelRcppThreadRdpackreshape2rgenoudrglrlangrmarkdownrngWELLRSpectrasassscalessensitivityshinyshinyjssourcetoolsSparseMstringistringrSuppDistssurvivaltibbletidyrtidyselecttimeDatetinytexTSclustTSdisttseriesTTRurcautf8vctrsviridisLitewithrxfunXMLxtablextsyamlzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Sensitivity Analysis Tools for LSD Simulations | LSDsensitivity-package LSDsensitivity |
| Elementary effects sensitivity analysis | elementary.effects.lsd |
| Stationarity and ergodicity tests | ergod.test.lsd |
| Fit a Kriging meta-model to a LSD model sample data | kriging.model.lsd |
| Find maximum and minimum meta-model responses | model.limits.lsd |
| Find optimal meta-model factor settings | model.optim.lsd |
| Predict meta-model response at given point(s) | model.pred.lsd |
| Fit a polynomial meta-model to a LSD model sample data | polynomial.model.lsd |
| Read a set of experimental data from a LSD model | read.doe.lsd |
| Generate the meta-model 3D response surface data | response.surface.lsd |
| Sobol variance decomposition sensitivity analysis | sobol.decomposition.lsd |
| Unimodality and symmetry tests | symmet.test.lsd |
