statis_FreeSort: Performs the STATIS method on Free Sorting data

In ClustBlock: Clustering of Datasets

Performs the STATIS method on Free Sorting data

Description

STATIS method on Free Sorting data. A lot of supplementary informations are also computed

Usage

statis_FreeSort(Data, NameSub=NULL, Graph_obj=TRUE, Graph_weights=TRUE)

Arguments

Data	data frame or matrix. Corresponds to all variables that contain subjects results. Each column corresponds to a subject and gives the groups to which the products (rows) are assigned
NameSub	string vector. Name of each subject. Length must be equal to the number of clumn of the Data. If NULL, the names are S1,...Sm. Default: NULL
Graph_obj	logical. Show the graphical representation od the objects? Default: TRUE
Graph_weights	logical. Should the barplot of the weights be plotted? Default: TRUE

Value

a list with:

a list with:

• RV: the RV matrix: a matrix with the RV coefficient between subjects

• compromise: a matrix which is the compromise of the subjects (akin to a weighted average)

• weights: the weights associated with the subjects to build the compromise

• lambda: the first eigenvalue of the RV matrix

• overall error : the error for the STATIS criterion

• error_by_conf: the error by configuration (STATIS criterion)

• rv_with_compromise: the RV coefficient of each subject with the compromise

• homogeneity: homogeneity of the subjects (in percentage)

• coord: the coordinates of each object

• eigenvalues: the eigenvalues of the svd decomposition

• inertia: the percentage of total variance explained by each axis

• error_by_obj: the error by object (STATIS criterion)

• scalefactors: the scaling factors of each subject

• proj_config: the projection of each object of each subject on the axes: presentation by subject

• proj_objects: the projection of each object of each subject on the axes: presentation by object

References

• Lavit, C., Escoufier, Y., Sabatier, R., Traissac, P. (1994). The act (statis method). Computational 462 Statistics & Data Analysis, 18 (1), 97-119.\

• Llobell, F., Cariou, V., Vigneau, E., Labenne, A., & Qannari, E. M. (2018). Analysis and clustering of multiblock datasets by means of the STATIS and CLUSTATIS methods.Application to sensometrics. Food Quality and Preference, in Press.

See Also

preprocess_FreeSort, clustatis_FreeSort

Examples

data(choc)
res.sta=statis_FreeSort(choc)

ClustBlock documentation built on Aug. 30, 2023, 5:08 p.m.