minimum number of dimensions to interpret, by default 0
ncp.max
maximum number of dimensions to interpret, by default NULL which corresponds to the number of columns minus 2
scale
a boolean, if TRUE (value set by default) then data are scaled to unit variance
method
method used to estimate the number of components, "GCV" for the generalized cross-validation approximation or "Smooth" for the smoothing method (by default "GCV")
Value
Returns ncp the best number of dimensions to use (find the minimum or the first local minimum) and the
mean error for each dimension tested
References
Josse, J. and Husson, F. (2012). Selecting the number of components in PCA using cross-validation approximations. Computational Statistics and Data Analysis, 56, 1869-1879.