Package: SensMap
Type: Package
Title: Sensory and Consumer Data Mapping
Version: 0.6
Date: 2018-02-01
Author: Ibtihel Rebhi [aut, cre], Rihab Boubakri [ctb], Dhafer Malouche [ctb]
Maintainer: Ibtihel Rebhi <ibtihel.rebhi@enit.utm.tn>
URL: https://github.com/IbtihelRebhi/SensMap
Description: External preference mapping technique is commonly used in sensory analysis
field to connect consumer rating data that contains liking scores to sensory data
that incorporates sensory attributes' evaluations of the perceived products
Danzart(1998) (<doi:10.1006/fstl.1998.0373>). SensMap package provides the
mapping visualization from several features : options in dimension reduction methods
and prediction models ranging from linear to non linear regressions. A smoothed
version of the map performed using LOESS algorithm is available. A selection process
of map stability 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 also made available.
Depends: R (>= 3.0.0), stats, grDevices, graphics
Imports: doBy, lattice, FactoMineR, MCMCpack, factoextra, fields,
ggdendro, glmulti, mgcv, plotly, shiny, ggplot2
License: GPL (>= 2)
LazyData: TRUE
Suggests: testthat
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2018-02-01 13:01:49 UTC; Admin
Repository: CRAN
Date/Publication: 2018-02-01 16:05:11 UTC

Package: SensMap
Type: Package
Title: Sensory and Consumer Data Mapping
Version: 0.7
Date: 2022-06-29
Author: Ibtihel Rebhi [aut, cre],  Dhafer Malouche [ctb]
Maintainer: Ibtihel Rebhi <ibtihel.rebhi@enit.utm.tn>
URL: https://github.com/IbtihelRebhi/SensMap
Description: Provides Sensory and Consumer Data
mapping and analysis <doi:10.14569/IJACSA.2017.081266>. The mapping visualization is made available
from several features : options in dimension reduction methods and prediction models ranging from
linear to non linear regressions. A smoothed version of the map performed using locally weighted regression algorithm
is available. A selection process of map stability 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 also made available.
Depends: R (>= 4.0), stats, grDevices, graphics
Imports: doBy, lattice, FactoMineR, MCMCpack, factoextra, fields,
ggdendro, glmulti, mgcv, plotly, shiny, ggplot2, reshape2
License: GPL (>= 2)
LazyData: TRUE
Suggests: testthat
RoxygenNote: 7.1.2.9000
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2022-07-04 12:45:33 UTC; Ibtihel Rebhi
Repository: CRAN
Date/Publication: 2022-07-04 19:00:02 UTC