dstatis.inter: Dual STATIS method (interstructure stage)

In dad: Three-Way / Multigroup Data Analysis Through Densities

Dual STATIS method (interstructure stage)

Description

Performs the first stage (interstructure) of the dual STATIS method in order to describe a data folder, consisting of T groups of individuals on which are observed p variables. It returns an object of class dstatis.

Usage

dstatis.inter(xf, normed = TRUE, centered = TRUE, data.scaled = FALSE, nb.factors = 3,
      nb.values = 10, sub.title = "", plot.eigen = TRUE, plot.score = FALSE,
      nscore = 1:3, group.name = "group", filename = NULL)

Arguments

xf	object of class folder. Its elements are data frames with p numeric columns. If there are non numeric columns, there is an error. The t^{th} element (t = 1, \ldots, T) matches with the t^{th} group.
normed	logical. If TRUE (default), the scalar products are normed.
centered	logical. If TRUE (default), the scalar products are centered.
data.scaled	logical. If TRUE, the data of each group are centered and scaled. The analysis is then performed on the correlation matrices. If FALSE (default), the analysis is performed on the covariance matrices.
nb.factors	numeric. Number of returned principal scores (default nb.factors = 3).
nb.values	numerical. Number of returned eigenvalues (default nb.values = 10).
sub.title	string. If provided, the subtitle for the graphs.
plot.eigen	logical. If TRUE (default), the barplot of the eigenvalues is plotted.
plot.score	logical. If TRUE, the graphs of principal scores are plotted. A new graphic device is opened for each pair of principal scores defined by nscore argument.
nscore	numeric vector. If plot.score = TRUE, the numbers of the principal scores which are plotted. By default it is equal to nscore = 1:3. Its components cannot be greater than nb.factors.
group.name	string. Name of the grouping variable. Default: groupname = "group".
filename	string. Name of the file in which the results are saved. By default (filename = NULL) the results are not saved.

Details

The covariance matrices (if data.scale is FALSE) or correlation matrices (if TRUE) per group are computed. The matrix W of the scalar products between these covariance matrices is then computed.

To perform the STATIS method, see the function DSTATIS of the multigroup package.

Value

Returns an object of class dstatis, that is a list including:

inertia	data frame of the eigenvalues and percentages of inertia.
contributions	data frame of the contributions to the first nb.factors principal components.
qualities	data frame of the qualities on the first nb.factors principal factors.
scores	data frame of the first nb.factors scores of the spectral decomposition of W.
norm	vector of the L^2 norms of the densities.
means	list of the means.
variances	list of the covariance matrices.
correlations	list of the correlation matrices.
skewness	list of the skewness coefficients.
kurtosis	list of the kurtosis coefficients.

Author(s)

Rachid Boumaza, Pierre Santagostini, Smail Yousfi, Gilles Hunault, Sabine Demotes-Mainard

References

Lavit, C., Escoufier, Y., Sabatier, R., Traissac, P. (1994). The ACT (STATIS method). Computational Statistics & Data Analysis, 18 (1994), 97-119.

See Also

print.dstatis, plot.dstatis, interpret.dstatis.

DSTATIS

Examples

data(roses)
rosesf <- as.folder(roses[,c("Sha","Den","Sym","rose")])

# Dual STATIS on the covariance matrices
result1 <- dstatis.inter(rosesf, data.scaled = FALSE, group.name = "rose")
print(result1)
plot(result1)

# Dual STATIS on the correlation matrices
result2 <- dstatis.inter(rosesf, data.scaled = FALSE, group.name = "rose")
print(result2)
plot(result2)

dad documentation built on Aug. 30, 2023, 5:06 p.m.