SensoMineR (version 1.27)

pmfa: Procrustean Multiple Factor Analysis (PMFA)

Description

Performs Multiple Factor Analysis combined with Procrustean Analysis.

Usage

pmfa(matrice, matrice.illu = NULL, mean.conf = NULL, dilat = TRUE,
      graph.ind = TRUE, graph.mfa = TRUE, lim = c(60,40), coord = c(1,2), cex = 0.8)

Value

Returns the RV coefficient between each individual configuration and the consensus.

If mean.conf is NULL (and graph.mfa is TRUE), returns the usual graphs resulting from the MFA function: the graph of the individuals and their partial representations, the graph of the variables (i.e. the coordinates of the products given by each panelist).

If mean.conf is not NULL returns the configuration input by the user.

When matrice.illu is not NULL, returns a graph of illustrative variables.

Returns as many superimposed representations of individual configurations as there are panelists.

Arguments

matrice

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

matrice.illu

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

mean.conf

coordinates of the average configuration (by default NULL, the average configuration is generated by MFA)

dilat

boolean, if TRUE (which is the default value) the Morand's dilatation is used

graph.ind

boolean, if TRUE (which is the default value) superimposes each panelist's configuration on the average configuration

graph.mfa

boolean, if TRUE (which is the default value) and if mean.conf = NULL the graphs of the MFA are drawn

lim

size of the tablecothe

coord

a length 2 vector specifying the components to plot

cex

cf. function par in the graphics package

Author

Francois Husson, Sebastien Le

Details

Performs first Multiple Factor Analysis on the tableclothes, then GPA in order to superimpose as well as possible panelist's configuration on the average configuration obtained by MFA (in the case where mean.conf is NULL). If mean.conf is not NULL the configuration used is the one input by the user.

References

Morand, E., Pages, J. Procrustes multiple factor analysis to analyze the overall perception of food products. Food Quality and Preference 14, 182-188.

See Also

MFA, nappeplot, indscal

Examples

if (FALSE) {
data(napping)
nappeplot(napping.don)
dev.new()
pmfa(napping.don, napping.words)
}