If you have a symmetric matrix, you can work with the upper triangle
instead of the lower one, and you get what you want by simply using
as.vector(A[upper.tri(A)])
Example:
> a = matrix(rnorm(16), 4, 4)
> A = a + t(a)
> A
[,1] [,2] [,3] [,4]
[1,] 0.3341294 0.5460334 -0.4388050 1.09415343
[2,] 0.5460334 0.1595501 0.3907721 0.24021833
[3,] -0.4388050 0.3907721 -0.4024922 -1.62140865
[4,] 1.0941534 0.2402183 -1.6214086 0.03987924
> as.vector(A[upper.tri(A)])
[1] 0.5460334 -0.4388050 0.3907721 1.0941534 0.2402183 -1.6214086
No need to play with potentially error-prone index vectors; upper.tri
does that for you.
Hope this helps,
Peter
On Fri, Jan 30, 2015 at 3:03 PM, Steven Yen <sye...@gmail.com> wrote:
> Dear
> I use sm2vec from package corpcor to puts the lower triagonal entries of a
> symmetric matrix (matrix A) into a vector. However, sm2vec goes downward
> (columnwise, vector B), but I would like it to go across (rowwise). So I
> define a vector to re-map the vector (vector C). This works. But is there a
> short-cut (simpler way)? Thank you.
>
>> A<-cor(e); A
> [,1] [,2] [,3] [,4] [,5] [,6]
> [1,] 1.00000000 0.5240809 0.47996616 0.11200672 -0.1751103 -0.09276455
> [2,] 0.52408090 1.0000000 0.54135982 -0.15985028 -0.2627738 -0.14184545
> [3,] 0.47996616 0.5413598 1.00000000 -0.06823105 -0.2046897 -0.23815967
> [4,] 0.11200672 -0.1598503 -0.06823105 1.00000000 0.2211311 0.08977677
> [5,] -0.17511026 -0.2627738 -0.20468966 0.22113112 1.0000000 0.23567235
> [6,] -0.09276455 -0.1418455 -0.23815967 0.08977677 0.2356724 1.00000000
>> B<-sm2vec(A); B
> [1] 0.52408090 0.47996616 0.11200672 -0.17511026 -0.09276455
> [6] 0.54135982 -0.15985028 -0.26277383 -0.14184545 -0.06823105
> [11] -0.20468966 -0.23815967 0.22113112 0.08977677 0.23567235
>> jj<-c(1,2,6,3,7,10,4,8,11,13,5,9,12,14,15)
>> C<-B[jj]; C
> [1] 0.52408090 0.47996616 0.54135982 0.11200672 -0.15985028
> [6] -0.06823105 -0.17511026 -0.26277383 -0.20468966 0.22113112
> [11] -0.09276455 -0.14184545 -0.23815967 0.08977677 0.23567235
>
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