I'm a bit clumsy about many things in R. Here's my problem. I'm trying
to build a square sparse matrix and populate it without looping (bad
practice, right). I have vectors of matched row/column pairs for which
the matrix entries have common characteristics and am look for a way to
fill the entries. So, if the matrix is A[20 by 20], and I might have rows
iRows <- c(2,3,4,6,7,8,10,11,12,14,15,16,18,19)
and columns
iCols <- c(1,2,3,5,6,7,9,10,11,13,14,15,17,18)
and you see these are most of the subdiagonal terms in A from rows 2-19.
They are all calculated in a similar way using values from a data frame
in which the terms are generally in iRows and iCols.
I could loop through each pair and all's well, but my question is
whether there's an R-certified alternative, that will speed things up
when the matrix is much larger (it will be - this is a prototype).
Any thoughts?
David S
--
David K Stevens, P.E., Ph.D., Professor
Civil and Environmental Engineering
Utah Water Research Laboratory
8200 Old Main Hill
Logan, UT 84322-8200
435 797 3229 - voice
435 797 1363 - fax
david.stev...@usu.edu
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