# R-alpha: Eigenvalue Computation Query

**Friedrich Leisch
**
Friedrich.Leisch@ci.tuwien.ac.at

*Tue, 20 May 1997 09:26:06 +0200*

>>>>>* On Tue, 20 May 1997 08:18:22 +0200,
*>>>>>* Kurt Hornik wrote:
*
>>>>>* Ross Ihaka writes:
*>>* I have been looking at the "eigen" function and have reintroduced the
*>>* ability to compute (right) eigenvalues and vectors for non-symmetric
*>>* matrices. I've also made "eigen" complex capable.
*
>>* The code is based on the eispack entry points RS, RG, CH, CG (which is
*>>* what S appears to use too). The problem with both the S and R
*>>* implementations is that they consume huge amounts of memory. Some of
*>>* this is due to purely ".Fortran" overhead, which I think I can cure.
*>>* But some of the bloat is due to the inclusion of special eigenvalues-only
*>>* code from eispack.
*
>>* The question is:
*
>>* Should I drop this special code and always compute both eigenvalues
*>>* and eigenvectors? This would substantially reduce code size, but might
*>>* increase computational cost in the case where only eigenvalues are
*>>* needed.
*
>* I'd say, reduce code size.
*
probably one shouldn't disagree with his boss openly ... but we
are the ones actually doing all the simulations :-)
do you know how much the difference in computational cost is? if it's
worth the increase in code size I'd rather prefer only computing the
required eigenvalues
best,
fritz
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