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-4.5)SensMap_0.3.zip(r-4.4)SensMap_0.3.zip(r-4.3)
SensMap_0.3.tgz(r-4.4-any)SensMap_0.3.tgz(r-4.3-any)
SensMap_0.3.tar.gz(r-4.5-noble)SensMap_0.3.tar.gz(r-4.4-noble)
SensMap_0.3.tgz(r-4.4-emscripten)SensMap_0.3.tgz(r-4.3-emscripten)
SensMap.pdf |SensMap.html✨
SensMap/json (API)

Peer review:

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

On CRAN:

4 exports 0.63 score 133 dependencies 4 scripts 178 downloads

Last updated 7 years agofrom:9cd26c00b0. Checks:OK: 1 ERROR: 6. Indexed: yes.

Exports:PrefMapSensMapUISmoothMapStabMap

Dependencies:abindaskpassbackportsbase64encbootbroombslibcachemcarcarDatacliclustercodacolorspacecommonmarkcorrplotcowplotcpp11crayoncrosstalkcurldata.tabledendextendDerivdigestdoBydotCall64dplyrDTellipseemmeansestimabilityevaluatefactoextraFactoMineRfansifarverfastmapfieldsflashClustfontawesomefsgenericsggdendroggfortifyggplot2ggpubrggrepelggsciggsignifglmultigluegridExtragtablehighrhtmltoolshtmlwidgetshttpuvhttrisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevalleapslifecyclelme4magrittrmapsMASSMatrixMatrixModelsmcmcMCMCpackmemoisemgcvmicrobenchmarkmimeminqamodelrmultcompViewmunsellmvtnormnlmenloptrnnetnumDerivopensslpbkrtestpillarpkgconfigplotlyplyrpolynompromisespurrrquantregR6rappdirsRColorBrewerRcppRcppEigenreshape2rJavarlangrmarkdownrstatixsassscalesscatterplot3dshinysourcetoolsspamSparseMstringistringrsurvivalsystibbletidyrtidyselecttinytexutf8vctrsviridisviridisLitewithrxfunxtableyaml