multigroup (version 0.4.5)

BGC: Between Group Comparison

Description

Between Group Comparison (BGC)

Usage

BGC(Data, Group, numc = NULL, ncomp = NULL, Scale = FALSE, graph = FALSE)

Arguments

Data

a numeric matrix or data frame

Group

a vector of factors associated with group structure

numc

number of components assocaited with PCA on each group

ncomp

number of components, if NULL number of components is equal to 2

Scale

scaling variables, by defalt is FALSE. By default data are centered within groups

graph

should loading and component be plotted

Value

list with the following results:

Data

Original data

Con.Data

Concatenated centered data

split.Data

Group centered data

Group

Group as a factor vector

loadings.common

Matrix of common loadings

lambda

The specific variances of groups

exp.var

Percentages of total variance recovered associated with each dimension

References

W. J. Krzanowski (1979). Between-groups comparison of principal components, Journal of the American Statistical Association, 74, 703-707.

A. Eslami, E. M. Qannari, A. Kohler and S. Bougeard (2013). General overview of methods of analysis of multi-group datasets, Revue des Nouvelles Technologies de l'Information, 25, 108-123.

A. Eslami, E. M. Qannari, A. Kohler and S. Bougeard (2013). Analyses factorielles de donnees structurees en groupes d'individus, Journal de la Societe Francaise de Statistique, 154(3), 44-57.

See Also

mgPCA, FCPCA, DCCSWA, DSTATIS, DGPA, summarize, TBWvariance, loadingsplot, scoreplot, iris

Examples

# NOT RUN {
Data = iris[,-5]
Group = iris[,5]
res.BGC = BGC(Data, Group, graph=TRUE)
loadingsplot(res.BGC, axes=c(1,2))
scoreplot(res.BGC, axes=c(1,2)) 
# }