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"John Randall" <[EMAIL PROTECTED]> writes:
> You are using LAPACK correctly. The problems are:
Well, almost. :-)
> v=:{."1 (2{::dgeev_jlapack_ m2) NB. principal eigenvector
> v
> 0.414299 0.731056 0.106322 0.53161
I've still got to learn these doubly inflected symbols (map and fetch),
but I confused myself by thinking I was looking for row, not column,
vectors.
Had I seen I was only off by a constant factor, I wouldn't have
worried, and I might even have discovered his normalization.
I'm curious, though: is there a reason you knew to take the right
eigenvector instead of the left except that it was clearly the one that
was a multiple of Coyle's? If I try to apply this elsewhere, I won't
have the fortune of having the answer.
> (a) The original matrix is wrong.
What do you mean by this? I think I missed something.
> (b) Coyle's data is weirdly normalized.
Based on what he's using it for, I can see him normalizing the sum of
the components rather than the magnitude of the vector. Non-technical
clients will likely understand each element as what fraction of their
total value applies to each component.
Thanks to everyone who replied; this was quick and useful help!
Bill
- --
Bill Harris http://facilitatedsystems.com/weblog/
Facilitated Systems Everett, WA 98208 USA
http://facilitatedsystems.com/ phone: +1 425 337-5541
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