The ade4 Package - NexTag Supports Open Source Initiatives

pcaivortho 197
Arguments
dudi
df
scannf
nf
a duality diagram, object of class dudi
a data frame with the same rows
a logical value indicating whether the eigenvalues bar plot should be displayed
if scannf FALSE, an integer indicating the number of kept axes
Value
an object of class ’pcaivortho’ sub-class of class dudi
rank
nf
eig
lw
cw
Y
X
tab
c1
as
ls
li
l1
co
param
an integer indicating the rank of the studied matrix
an integer indicating the number of kept axes
a vector with the all eigenvalues
a numeric vector with the row weigths (from dudi)
a numeric vector with the column weigths (from dudi)
a data frame with the dependant variables
a data frame with the explanatory variables
a data frame with the modified array (projected variables)
a data frame with the Pseudo Principal Axes (PPA)
a data frame with the Principal axis of dudi$tab on PAP
a data frame with the projection of lines of dudi$tab on PPA
a data frame dudi$ls with the predicted values by X
a data frame with the Constraint Principal Components (CPC)
a data frame with the inner product between the CPC and Y
a data frame containing a summary
Author(s)
Daniel Chessel
Anne B Dufour 〈dufour@biomserv.univ-lyon1.fr〉
References
Rao, C. R. (1964) The use and interpretation of principal component analysis in applied research.
Sankhya, A 26, 329–359.
Sabatier, R., Lebreton J. D. and Chessel D. (1989) Principal component analysis with instrumental
variables as a tool for modelling composition data. In R. Coppi and S. Bolasco, editors. Multiway
data analysis, Elsevier Science Publishers B.V., North-Holland, 341–352