acp {amap} | R Documentation |
Principal component analysis
acp(x,center=TRUE,reduce=TRUE,wI=rep(1,nrow(x)),wV=rep(1,ncol(x))) pca(x,center=TRUE,reduce=TRUE,wI=rep(1,nrow(x)),wV=rep(1,ncol(x))) ## S3 method for class 'acp' print(x, ...)
x |
Matrix / data frame |
center |
a logical value indicating whether we center data |
reduce |
a logical value indicating whether we "reduce" data i.e. divide each column by standard deviation |
wI,wV |
weigth vector for individuals / variables |
... |
arguments to be passed to or from other methods. |
This function offer a variant of princomp
and
prcomp
functions, with a slightly different
graphic representation (see plot.acp
).
An object of class acp The object is a list with components:
sdev |
the standard deviations of the principal components. |
loadings |
the matrix of variable loadings (i.e., a matrix
whose columns contain the eigenvectors). This is of class
|
scores |
if |
eig |
Eigen values |
Antoine Lucas, http://mulcyber.toulouse.inra.fr/projects/amap/
A. Carlier Analyse des donn\'ees Multidimensionnelles http://www.lsp.ups-tlse.fr/Carlier/enseignement.html
data(lubisch) lubisch <- lubisch[,-c(1,8)] p <- acp(lubisch) plot(p)