Dear Thomas
Yes, you're right. But I'm looking for this not only for computational cost
reasons.
eigen function from R has identical behavior to matlab function eig, but not
to eigs.
Even in matlab you can check that those function are not giving identical
results.
Here you have a short example :
Suppose we have given a matrix M
M =
1.2607 -3.5575 2.2968 0 0 0
-3.5575 10.1429 -6.5855 0 0 0
2.2968 -6.5855 4.2887 0 0 0
0 0 0 2.6359 -4.8489 2.2130
0 0 0 -4.8489 8.9217 -4.0728
0 0 0 2.2130 -4.0728 1.8598
For eig (R's eigen)we have:
[V,eiggg]=eig(M);
V =
0.5774 0 0 -0.7663 0 0.2820
0.5774 0 0 0.1389 0 -0.8046
0.5774 0 0 0.6273 0 0.5226
0 0.5774 -0.6857 0 0.4432 0
0 0.5774 -0.0410 0 -0.8155 0
0 0.5774 0.7267 0 0.3723 0
eiggg =
-0.0000 0 0 0 0 0
0 -0.0000 0 0 0 0
0 0 0.0011 0 0 0
0 0 0 0.0252 0 0
0 0 0 0 13.4163 0
0 0 0 0 0 15.6671
And for matlab's eigs we have:
[Y,eigenvals] = eigs(M,4,0,options) ;
Y =
-0.8147 -0.0106 -0.0000 -0.5774
0.3802 -0.0143 -0.0000 -0.5774
0.4344 0.0249 0.0000 -0.5774
-0.0332 0.6871 -0.5774 0.0000
0.0430 0.0379 -0.5774 0.0000
-0.0098 -0.7250 -0.5774 0.0000
eigenvals =
0.0331 0 0 0
0 0.0011 0 0
0 0 0.0000 0
0 0 0 -0.0000
As you can see, columns of chosen eigenvectors are different. I'm looking
for function similar to eigs in R. I'll try with svd, which you have
mentioned. Thank you for that idea, maybe it will be what i'm looking for.
Kayteck
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