On 21-04-2012, at 16:40, peter dalgaard wrote:
>
> On Apr 21, 2012, at 15:22 , Luke Hartigan wrote:
>
>> Hi all,
>>
>> In my experience, using eigen to solve generalized eigenvalue / eigenvector
>> problems only gives correct looking eigenvalues while the eigenvectors seem
>> to be wrong (in comparison to results from MATLAB's 'eig' function for
>> example).
>
> Could you please document that? There are many misconceptions about when
> eigenvectors are "correct" and platform dependencies too. As far as I can
> tell, both R and Matlab use the same LAPACK routines.
The OP posted two matrices:
A <- matrix(c(1457.738, 1053.181, 1256.953,
1053.181, 1213.728, 1302.838,
1256.953, 1302.838, 1428.269), nrow=3, byrow=TRUE)
B <- matrix(c(4806.033, 1767.480, 2622.744,
1767.480, 3353.603, 3259.680,
2622.744, 3259.680, 3476.790), nrow=3, byrow=TRUE)
I've tried
eigen(solve(B)%*%A)
(which is probably not the best way to handle this problem numerically) to
approximate the generalized ev problem.
And the geigen function
geigen(A,B,TRUE,TRUE)
The eigenvalues are identical upto the printed 9 digits but the eigenvectors
appear to be quite different.
Maybe this is what Luke meant.
Berend
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
