Package: SensMap 0.3

SensMap: Sensory and Consumer Data Mapping

External preference mapping technique is commonly used in sensory analysis field to explain consumer preferences in function of sensory attributes of products Danzart(1998) (<doi:10.1006/fstl.1998.0373>). The package provides map visualization with options in dimension reduction methods and prediction models from linear and non linear regressions. A smoothed version of the map performed using LOESS algorithm is available. A comparison approach of maps stability from different features before and after smoothing is provided. A 'shiny' application is included. It presents an easy GUI for the implemented functions as well as a comparative tool of fit models using several criteria. Basic analysis such as characterization of products, panelists and sessions likewise consumer segmentation are available.

Authors:Ibtihel Rebhi [aut, cre], Rihab Boubakri [ctb], Dhafer Malouche [ctb]

SensMap_0.3.tar.gz
SensMap_0.3.zip(r-4.7-any)SensMap_0.3.zip(r-4.6-any)SensMap_0.3.zip(r-4.5-any)
SensMap_0.3.tgz(r-4.6-any)SensMap_0.3.tgz(r-4.5-any)
SensMap_0.3.tar.gz(r-4.7-any)SensMap_0.3.tar.gz(r-4.6-any)
SensMap_0.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
SensMap/json (API)

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

Bug tracker:https://github.com/ibtihelrebhi/sensmap/issues

Uses libs:
  • openjdk– OpenJDK Java runtime, using Hotspot JIT
Datasets:

On CRAN:

Conda:

openjdk

2.70 score 1 scripts 248 downloads 4 exports 144 dependencies

Last updated from:9cd26c00b0. Checks:7 ERROR, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develERROR212
source / vignettesOK259
linux-releaseERROR164
macos-releaseERROR195
macos-oldrelERROR277
windows-develERROR141
windows-releaseERROR160
windows-oldrelERROR152
wasm-releaseOK143

Exports:PrefMapSensMapUISmoothMapStabMap

Dependencies:abindaskpassbackportsbase64encbootbroombslibcachemcarcarDatacliclustercodacolorspacecommonmarkcorrplotcowplotcpp11crosstalkcurldata.tabledendextendDerivdigestdoBydotCall64dplyrDTellipseemmeansestimabilityevaluatefactoextraFactoMineRfarverfastmapfieldsflashClustfontawesomeforecastFormulafracdifffsgenericsggdendroggfortifyggplot2ggpubrggrepelggsciggsignifglmultigluegridExtragtablehighrhtmltoolshtmlwidgetshttpuvhttrirlbaisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevalleapslifecyclelme4lmtestmagrittrmapsMASSMatrixMatrixModelsmcmcMCMCpackmemoisemgcvmimeminqamodelrmultcompViewmvtnormnlmenloptrnnetnumDerivopensslotelpbkrtestpillarpkgconfigplotlypolynompromisespurrrquantregR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrJavarlangrmarkdownrstatixS7sassscalesscatterplot3dshinyshowtextshowtextdbsourcetoolsspamSparseMstringistringrsurvivalsyssysfontstibbletidyrtidyselecttimeDatetinytexurcautf8vctrsviridisviridisLitewithrxfunxtableyamlzoo