Sensory data analysis with R

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Documentation for package ‘SensoMineR’ version 1.15

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ardi Automatic Research of DIvergences between scores
averagetable Computes a (products,descriptors) matrix
barrow Barplot per row with respect to a set of quantitative variables
boot Simulate virtual panels for several functions
boxprod Boxplot per category with respect to a categorical variable and a set of quantitative variables
cards Cards
carto Preference Mapping Techniques
cartoconsumer Preference Mapping Techniques and segmentation of consumers
chocolates Chocolates data
cocktail Cocktail data
coltable Color the cells of a data frame according to 4 threshold levels
compo.cocktail Composition of the cocktails data
construct.axes Coordinates of individuals and illustrative individuals for PCA or MFA
cpa Consumers' Preferences Analysis
decat DEscription of CATegories
fahst Factorial Approach for Hierarchical Sorting Task data
fasnt Factorial Approach for Sorting Napping Task data
fast Factorial Approach for Sorting Task data
fcp Free choice profiling
forprefmap Creates the dataset for the _carto_ function by considering Ideal Profile data
graphinter Graphical display of the interaction between two qualitative variables
hedo.cocktail Cocktails hedonic scores
hedo.consist Hedonic consistency of the ideal data
hedochoc Chocolates hedonic scores
histprod Histogram for each descriptor
hsortplot Plot consumers' hierarchical sorting
ideal.sd Variability in the ideal data compared to the perceived intensities
IdMap Ideal Mapping (IdMap)
indscal Construct the Indscal model for Napping data type
influence.ideal Influence of the perception of a product on the ideal rating
interact Estimation of interaction coefficients
magicsort Returns a sorted data matrix
multi.ideal Single vs. Multiple Ideal
nappeplot Plot panelists' tableclothe
nappesortplot Plot consumers' sorted tablecloth
napping Napping data
napping.don An example of Napping data
napping.words An example of "illustrative" variables to enhance results from Napping data
optimaldesign Construction of an optimal design
paneliperf Panelists' performance according to their capabilities to dicriminate between products
panellipse Confidence ellipses around products based on panelists descriptions
panellipse.session Repetability of panelists descriptions studied by confidence ellipses around products per session
panelmatch Confidence ellipses around products based on panel descriptions
panelperf Panel's performance according to its capabilities to dicriminate between products
perfume Perfume
perfume_fcp Perfume data obtained by free choice profiling
perfume_ideal Perfume Ideal Data
plot.fahst Make Factorial Approach for Hierarchical Sorting Task data (FAHST) graphs
plot.fasnt Make Factorial Approach for Sorting Napping Task data (FASNT) graphs
plot.fast Make Factorial Approach for Sorting Task data (FAST) graphs
plot.IdMap Plot for the Ideal Mapping
plotpanelist Plotpanelist
pmfa Procrustean Multiple Factor Analysis (PMFA)
print.fahst Print Factorial Approach for Hierarchical Sorting Task data (FAHST) results
print.fasnt Print Factorial Approach for Sorting Napping Task data (FASNT) results
print.fast Print Factorial Approach for Sorting Task data (FAST) results
scalebypanelist Scale by panelist
search.desc Search for discriminating descriptors
senso.cocktail Sensory data for 16 cocktails
senso.consist Sensory consistency of the ideal data
sensochoc Sensory data for 6 chocolates
sensopanels Sensory profiles given by 7 panels
smoothies Smoothies
triangle.design Construct a design for triangle tests
triangle.pair.test Make a Triangle test for two products
triangle.test Make a Triangle test for a set of products