Memory Efficiency of Symmetric Matrix
the SparseM package might be what you are looking for http://www.econ.uiuc.edu/~roger/research/sparse/SparseM.pdf
On Jan 7, 11:36?am, S?ren H?jsgaard <Soren.Hojsga... at agrsci.dk> wrote:
You can do mat[lower.tri(mat, diag=F)] S?ren
________________________________ Fra: r-help-boun... at r-project.org p? vegne af Nathan S. Watson-Haigh Sendt: on 07-01-2009 01:28 Til: r-h... at r-project.org Emne: [R] Memory Efficiency of Symmetric Matrix -----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I'm generating a symmetric correlation matrix using a data matrix as input: mat <- cor(data.mat) My question is: Is there a more memory efficient way to store this data? For instance, since: all(mat == t(mat)) every value is duplicated, and I should be able to almost half the memory usage for large matrices. Any thoughts/comments? Cheers, Nathan - -- - -------------------------------------------------------- Dr. Nathan S. Watson-Haigh OCE Post Doctoral Fellow CSIRO Livestock Industries Queensland Bioscience Precinct St Lucia, QLD 4067 Australia Tel: +61 (0)7 3214 2922 Fax: +61 (0)7 3214 2900 Web:http://www.csiro.au/people/Nathan.Watson-Haigh.html - -------------------------------------------------------- -----BEGIN PGP SIGNATURE----- Version: GnuPG v1.4.9 (MingW32) Comment: Using GnuPG with Mozilla -http://enigmail.mozdev.org<http://enigmail.mozdev.org/> iEYEARECAAYFAklj9yAACgkQ9gTv6QYzVL6MGQCg1CHsRGAwEMah/8ZuZ9QFI6O5 lcIAnjZ68DE9FABLMd07A3AfdMPRpXIH =5bet -----END PGP SIGNATURE----- ______________________________________________ R-h... at r-project.org mailing listhttps://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guidehttp://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-h... at r-project.org mailing listhttps://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guidehttp://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.