>>>>> William Dunlap
>>>>> on Thu, 17 May 2018 11:28:50 -0700 writes:
> Your explanation needs to be a bit more general in the
> case of identical eigenvalues - each distinct eigenvalue
> has an associated subspace, whose dimension is the number
> repeats of that eigenvalue and the eigenvectors for that
> eigenvalue are an orthonormal basis for that subspace.
> (With no repeated eigenvalues this gives your 'unique up
> to sign'.)
Thank you, Bill, notably for the concrete example of non-trivial
eigenspaces (per eigenvector).
Note I did say
"... such that at least for the good cases where all eigenspaces
are 1-dimensional, ..."
knowing well that only in that case it "is easy".
I have a gut feeling but may be wrong that such simplistic post
processing may also help (to get cross-platform reproducibility)
in the case of MASS::mvrnorm() where repeated eigenvalues will
be common in practice.
Martin
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