Learn R Programming

SensoMineR (version 1.27)

fasnt: Factorial Approach for Sorting Napping Task data

Description

Perform Factorial Approach for Sorting Napping Task data (FASNT) on a table where the rows (i) are products and the columns (j) are for each consumer the coordinates of the products on the tablecloth associated with napping on the one hand and the partitionning variable associated with categorization on the other hand. The columns are grouped by consumer. For the partitionning variable, the label associated with a group can be an arbirary label (for example G1 for group 1, etc.) or the words associated with the group in the case of qualified sorted napping.

Usage

fasnt(don,first="nappe",B=100,axes=c(1,2),alpha=0.05,ncp=5,
     graph=TRUE,name.group=NULL,sep.word=" ",word.min=5,ncp.boot=2)

Value

A list containing the following elements:

eig

a matrix containing all the eigenvalues, the percentage of variance and the cumulative percentage of variance

ind

a list of matrices containing all the results for the products (coordinates, square cosine, contributions)

quali.var

a list of matrices containing all the results for the categories of categorization (coordinates, square cosine, contributions, v.test)

quanti.var

a list of matrices containing all the results for the napping (coordinates, square cosine, contributions, v.test)

group

a list of matrices containing all the results for consumers (coordinates, square cosine, contributions)

indicator

a list of matrices containing different indicators for napping and categorization

textual

the results of the textual analysis for the products

call

a list with some statistics

Arguments

don

a data frame with n rows (products) and p columns (assesor : categorical variables)

first

2 possibilities: "nappe" if the napping variables first appear for each consumer or "catego" if it is the categorization variable

B

the number of simulations (corresponding to the number of virtual panels) used to compute the ellipses

axes

a length 2 vector specifying the components to plot

alpha

the confidence level of the ellipses

ncp

number of dimensions kept in the results (by default 5)

graph

boolean, if TRUE a graph is displayed

name.group

a vector containing the name of the consumers (by default, NULL and the group are named J1, J2 and so on)

sep.word

the word separator character in the case of qualified sorted napping

word.min

minimum sample size for the word selection in textual analysis

ncp.boot

number of dimensions used for the Procrustean rotations to build confidence ellipses (by default 2)

Author

Marine Cadoret, Sebastien Le sebastien.le@institut-agro.fr

References

Pag\`es, J., Le, S., Cadoret, M. (2010) The Sorted Napping: a new holistic approach in sensory evaluation. Journal of Sensory Studies
Cadoret, M., Le, S., Pages, J. (2009) Combining the best of two worlds, the "sorted napping". SPISE. Ho Chi Minh City, Vietnam

Examples

Run this code
if (FALSE) {
data(smoothies)
## Example of FASNT results
res.fasnt<-fasnt(smoothies,first="nappe",sep.word=";")
}

Run the code above in your browser using DataLab