Package: multisensi 2.1-1

Hervé Monod

multisensi: Multivariate Sensitivity Analysis

Functions to perform sensitivity analysis on a model with multivariate output.

Authors:Caroline Bidot <[email protected]>, Matieyendou Lamboni <[email protected]>, Hervé Monod <[email protected]>

multisensi_2.1-1.tar.gz
multisensi_2.1-1.tar.gz(r-4.7-any)multisensi_2.1-1.tar.gz(r-4.6-any)
multisensi_2.1-1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
multisensi/json (API)

# Install 'multisensi' in R:

install.packages('multisensi', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

biomasseX - A factorial input design for the main example
biomasseY - Output of the biomasse model for the plan provided in the package
Climat - Climate data

On CRAN:

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

2.57 score 1 stars 37 scripts 263 downloads 1 mentions 30 exports 81 dependencies

Last updated from:b5403a8150. Checks:2 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	NOTE	173
source / vignettes	OK	299
linux-release-x86_64	NOTE	156
wasm-release	OK	119

Exports:analysis.anoasg analysis.sensitivity basis.ACP basis.bsplines basis.mine basis.osplines basis.poly biomasse bspline dynsi graph.bar graph.pc grpe.gsi gsi multisensi multivar planfact planfact.as plot.dynsi plot.gsi predict.gsi print.dynsi print.gsi quality sesBsplinesNORM sesBsplinesORTHONORM simulmodel summary.dynsi summary.gsi yapprox

Dependencies:base64enc boot bslib cachem class cli clue cluster codetools commonmark cpp11 digest dplyr dtw dtwclust evaluate farver fastmap flexclust fontawesome foreach fs generics ggplot2 ggrepel glue gtable highr htmltools httpuv isoband iterators jquerylib jsonlite knitr labeling later lattice lifecycle magrittr MASS Matrix memoise mime modeltools numbers otel pillar pkgconfig plyr promises proxy R6 rappdirs RColorBrewer Rcpp RcppArmadillo RcppEigen RcppParallel RcppThread reshape2 rlang RSpectra S7 sass scales sensitivity shiny shinyjs sourcetools stringi stringr tibble tidyselect utf8 vctrs viridisLite withr xfun xtable yaml

Quick guide

Rendered frommultisensi-vignette.rnwusingknitr::knitr

Last update: 2018-04-10
Started: 2016-04-27

Citation

Readme and manuals

Help Manual

Help page	Topics
Multivariate sensitivity Analysis	multisensi-package
Runs a series of analyses of variance	analysis.anoasg
Runs a series of sensitivity analyses by a function from the 'sensitivity' package	analysis.sensitivity
A function to decompose multivariate data by principal components analysis (PCA)	basis.ACP
A function to decompose multivariate data on a B-spline basis	basis.bsplines
A function to decompose multivariate data on a user-defined basis	basis.mine
A function to decompose multivariate data on an orthogonal B-spline basis (O-spline)	basis.osplines
A function to decompose multivariate data on a polynomial basis	basis.poly
The Winter Wheat Dynamic Model	biomasse
A factorial input design for the main example	biomasseX
Output of the biomasse model for the plan provided in the package	biomasseY
function to evaluate B-spline basis functions	bspline
Climate data	Climat
Dynamic Sensitivity Indices: DSI	dynsi
Sensitivity index bar plot	graph.bar
Principal Components graph for gsi objects	graph.pc
Group factor GSI, obsolete function	grpe.gsi
Generalised Sensitivity Indices: GSI	gsi
A function with multiple options to perform multivariate sensitivity analysis	multisensi
A function to decompose the output data set and reduce its dimension	multivar
Complete factorial design in lexical order	planfact
Complete factorial design	planfact.as
Plot method for dynamic sensitivity results	plot.dynsi
Plot method for generalised sensitivity analysis	plot.gsi
A function to predict multivariate output	predict.gsi
print DYNSI	print.dynsi
print GSI	print.gsi
quality of any approximation	quality
normalized B-splines basis functions	sesBsplinesNORM
orthogonalized B-splines basis functions	sesBsplinesORTHONORM
Model simulation	simulmodel
dynsi summary	summary.dynsi
summary of GSI results	summary.gsi
Prediction based on PCA and anovas (NOT ONLY)	yapprox

Package: multisensi 2.1-1

multisensi: Multivariate Sensitivity Analysis

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)