'Is it possible in R to calculate all eigenvalues of a very large symmetric n by n dense matrix in blocks to conserve RAM?
To provide some context, I work with DNA methylation data that even after some filtering can still consist of 200K-300K features (with much less samples, about 500). I need to do some operations on this and I have been using the bigstatsr package for other operations, which can use a Filebacked Big Matrix (FBM) to determine for instance a crossproduct in blocks. I further found that this can work with RSpectra::eigs_sym to get a specified number of eigenvalues, but unfortunately not all. To get all eigenvalues I have mainly seen the base R eigen function being used, but with this I run out of RAM when I have a matrix that is 300k by 300k.
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