Description Usage Arguments Value References See Also Examples
Dual Common Component and Specific Weights Analysis: to find common structure among variables of different groups
1 |
Data |
a numeric matrix or data frame |
Group |
a vector of factors associated with group structure |
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 |
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 |
saliences |
Each group having a specific contribution to the determination of this common space, namely the salience, for each dimension under study |
lambda |
The specific variances of groups |
exp.var |
Percentages of total variance recovered associated with each dimension |
E. M. Qannari, P. Courcoux, and E. Vigneau (2001). Common components and specific weights analysis performed on preference data. Food Quality and Preference, 12(5-7), 365-368.
A. Eslami (2013). Multivariate data analysis of multi-group datasets: application to biology. University of Rennes I.
mgPCA
, FCPCA
, BGC
, DSTATIS
, DGPA
, summarize
, TBWvariance
, loadingsplot
, scoreplot
, iris
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