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SensMap  

Sensory and Consumer Data Mapping
View on CRAN: Click here


Download and install SensMap package within the R console
Install from CRAN:
install.packages("SensMap")

Install from Github:
library("remotes")
install_github("cran/SensMap")

Install by package version:
library("remotes")
install_version("SensMap", "0.7")



Attach the package and use:
library("SensMap")
Maintained by
Ibtihel Rebhi
[Scholar Profile | Author Map]
First Published: 2017-09-23
Latest Update: 2022-07-04
Description:
Provides Sensory and Consumer Data mapping and analysis . 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.
How to cite:
Ibtihel Rebhi (2017). SensMap: Sensory and Consumer Data Mapping. R package version 0.7, https://cran.r-project.org/web/packages/SensMap. Accessed 19 Apr. 2025.
Previous versions and publish date:
0.1 (2017-09-23 15:42), 0.2 (2017-09-25 19:38), 0.3 (2017-09-26 06:49), 0.4 (2017-09-30 18:20), 0.5 (2018-01-30 00:34), 0.6 (2018-02-01 17:05)
Other packages that cited SensMap R package
View SensMap citation profile
Other R packages that SensMap depends, imports, suggests or enhances
Complete documentation for SensMap
Functions, R codes and Examples using the SensMap R package
Some associated functions: PrefMap . SensMapUI . SmoothMap . StabMap . hedo_biscuit . sens_biscuit . 
Some associated R codes: Bayes_model.R . GAM_model.R . GLM_model.R . LOESS_smoothing.R . Polynomial-model.R . PrefMap.R . SmoothMap.R . StabMap.R . discrt_space.R . map_ca.R . map_mfa.R . map_pca.R . shinySensMap.R .  Full SensMap package functions and examples
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