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


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