I agree with Kasper, this is a 'big' issue. Does your method of taking only
n PCs reduce the load on memory?
The new addition to the summary looks like a good idea, but Proportion of
Variance as you describe it may be confusing to new users. Am I correct in
saying Proportion of variance describes
I agree with Kasper, this is a 'big' issue. Does your method of taking only
n PCs reduce the load on memory?
The new addition to the summary looks like a good idea, but Proportion of
Variance as you describe it may be confusing to new users. Am I correct in
saying Proportion of variance describes
Martin, I fully agree. This becomes an issue when you have big matrices.
(Note that there are awesome methods for actually only computing a small
number of PCs (unlike your code which uses svn which gets all of them);
these are available in various CRAN packages).
Best,
Kasper
On Thu, Mar 24, 2
Following from the R-help thread of March 22 on "Memory usage in prcomp",
I've started looking into adding an optional 'rank.' argument
to prcomp allowing to more efficiently get only a few PCs
instead of the full p PCs, say when p = 1000 and you know you
only want 5 PCs.
(https://stat.ethz.
