Ibtihel Rebhi [aut, cre], Rihab Boubakri [ctb], Dhafer Malouche [ctb]
Obtain external preference map to explain consumer preferences in function of sensory
attributes of products (K.Greenhoff et al. (1994) <doi:10.1007/978-1-4615-2171-6_6>)
with options in dimension reduction methods and prediction models from linear and non linear regressions.
A smoothed version of the map is available and a comparison of maps stability from different features
before and after smoothing is provided which may help industrials to make good decisions about characteristics
of new product development.
A 'shiny' application is included. It presents an easy GUI for
the implemented functions as well as a comparative tool of fit models
performance using several criteria. Basic analysis such as characterization
of products, panelists and sessions likewise consumers segmentation are available.
R (>= 3.0.0), stats, grDevices, graphics
ggfortify, doBy, lattice, FactoMineR, MCMCpack, factoextra,
fields, ggdendro, glmulti, mgcv, plotly, shiny, ggplot2

External preference mapping technique is commonly used in sensory analysis
field to explain consumer preferences in function of sensory attributes of products
Danzart (1998) (<https://www.lavoisier.fr/livre/agro-alimentaire/evaluation-
sensorielle-3e-ed/depledt/descriptif-9782743009977>). 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.

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.