Performs preference mapping techniques based on multidimensional exploratory data analysis.
carto(Mat, MatH, level =0, regmod =1, coord = c(1,2), asp =1, cex =1.3, col ="steelblue4", font =2, clabel =0.8, label.j =FALSE, resolution =200, nb.clusters =0, graph.tree=TRUE,graph.corr=TRUE,graph.carto=TRUE, main=NULL,col.min=7.5,col.max=0)
Arguments
Mat: a data frame corresponding to the axes of the map
MatH: a data frame in which each row represent a product and each column represent the hedonic scores of a given consumer for the products
level: the number of standard deviations used in the calculation of the preference response surface for all the consumers
regmod: the type of regression model used in the calculation of the preference response surface for all the consumers. regmod = 1: quadratic model, regmod = 2: vector model, regmod = 3: circular model, regmod = 4: elliptical model
coord: a vector of length 2, the rank of the axis used to display the results if "manual"
is not assigned to the option parameter
asp: if 1 is assigned to that parameter, the graphic displays are output in an orthonormal coordinate system
cex: cf. function par in the graphics package
col: cf. function par in the graphics package
font: cf. function par in the graphics package
clabel: cf. the ade4 package
label.j: boolean, if T then the labels of the panelists who gave the hedonic scores are displayed
resolution: resolution of the map
nb.clusters: number of clusters to use (by default, 0 and the optimal numer of clusters is calculated
graph.tree: boolean, if TRUE plots the tree in 2 dimensions
graph.corr: boolean, if TRUE plots the variables factor map
graph.carto: boolean, if TRUE plots the preference map
main: an overall title for the plot
col.min: define the color which match to the low levels of preference
col.max: define the color which match to the high levels of preference
Details
The preference mapping methods are commonly used in the fields of market research and research and development to explore and understand the structure and tendencies of consumer preferences, to link consumer preference information to other data and to predict the behavior of consumers in terms of acceptance of a given product.
This function refers to the method introduced by M. Danzart. A response surface is computed per consumer; then according to certain threshold preference zones are delimited and finally superimposed.
References
Danzart M., Sieffermann J.M., Delarue J. (2004). New developments in preference mapping techniques: finding out a consumer optimal product, its sensory profile and the key sensory attributes. 7th Sensometrics Conference, July 27-30, 2004, Davis, CA.