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.
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)Returns an object of class dstatis, that is a list including:
data frame of the eigenvalues and percentages of inertia.
data frame of the contributions to the first nb.factors principal components.
data frame of the qualities on the first nb.factors principal factors.
data frame of the first nb.factors scores of the spectral decomposition of \(W\).
vector of the \(L^2\) norms of the densities.
list of the means.
list of the covariance matrices.
list of the correlation matrices.
list of the skewness coefficients.
list of the kurtosis coefficients.
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.
logical. If TRUE (default), the scalar products are normed.
logical. If TRUE (default), the scalar products are centered.
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.
numeric. Number of returned principal scores (default nb.factors = 3).
numerical. Number of returned eigenvalues (default nb.values = 10).
string. If provided, the subtitle for the graphs.
logical. If TRUE (default), the barplot of the eigenvalues is plotted.
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.
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.
string. Name of the grouping variable. Default: groupname = "group".
string. Name of the file in which the results are saved. By default (filename = NULL) the results are not saved.
Rachid Boumaza, Pierre Santagostini, Smail Yousfi, Gilles Hunault, Sabine Demotes-Mainard
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.
Lavit, C., Escoufier, Y., Sabatier, R., Traissac, P. (1994). The ACT (STATIS method). Computational Statistics & Data Analysis, 18 (1994), 97-119.
print.dstatis, plot.dstatis, interpret.dstatis.
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)
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