indscal: Construct the Indscal model for Napping data type

Description Usage Arguments Value Author(s) References See Also Examples

Description

This version of the Indscal model is specially adapted to Napping data type, i.e. products (stimuli) are positioned on a tableclothe by panelists, then their coordinates are used as input for the Indscal model.

Usage

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indscal(matrice, matrice.illu = NULL, maxit = 200, coord = c(1,2), 
    eps = 1/10^5)

Arguments

matrice

a data frame of dimension (p,2j), where p represents the number of products and j the number of panelists (two coordinates per panelist)

matrice.illu

a data frame with illustrative variables (with the same row.names in common as in matrice)

maxit

the maximum number of iterations until the algorithm stops

coord

a length 2 vector specifying the components to plot

eps

a threshold with respect to which the algorithm stops, i.e. when the difference between the criterion function at step n and n+1 is less than eps

Value

Returns a list including:

W

a matrix with the subject coordinates

points

a matrix with the stimuli (individuals) coordinates

subvar

a vector with the strain between each configuration and the stimuli configuration

r2

the strain criterion

The functions returns the three following graphs:
A stimuli representation, ie. a representation of the products
A representation of the weights computed by the Indscal model.
A correlation circle of the variables enhanced by illustrative variables (supplementary columns)

Author(s)

Peter Ellis
Fran<e7>ois Husson

References

Carroll, J.D. & J.J. Chang (1970). Analysis of individual differences in multidimensional scaling via an N-way generalization of "Eckart-Young" decomposition. Psychometrika, 35, 283-319.

See Also

nappeplot, pmfa

Examples

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## Not run: 
data(napping)
nappeplot(napping.don)
resindscal<- indscal(napping.don, napping.words)
x11()
prefpls(cbind(resindscal$points, napping.words))
x11()
pmfa(napping.don, napping.words, mean.conf = resindscal$points)

## End(Not run)


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