External preference mapping technique is commonly used in sensory analysis
field to connect consumer rating data that contains liking scores to sensory data
that consists of 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 maps 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.
doBy, lattice, FactoMineR, MCMCpack, factoextra, fields,
ggdendro, glmulti, mgcv, plotly, shiny, ggplot2

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.

Ibtihel Rebhi [aut, cre],  Dhafer Malouche [ctb]
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.
doBy, lattice, FactoMineR, MCMCpack, factoextra, fields,
ggdendro, glmulti, mgcv, plotly, shiny, ggplot2, reshape2