At 14:40 04/11/2003, [EMAIL PROTECTED] wrote:

><If I consider an indefinte real matrix ...>
>I'm not familiar with the definition of an indefinite matrix.

I see it in Harville, D.A., Matrix algebra from a statistician's 
perspective. 1997, New-York: Springer-Verlag. 630.

it is a matrix A that is neither positive definite nor positive definite.

><I would like to know if the symmetry of the matrix is sufficient to say 
>that their eigenvectors are real ?>
>(I assume you mean the eigenvalues are real...)
>If A is a symmetric real valued matrix then the eignevalues of A are 
>real.  There is a short proof of this due to Styan that can be found, 
>among other places, in Searle's 'Matrix Algebra Useful for Statistics' and 
>alluded to in Anderson's Multivariate Analysis book in Chapter 11.
>
>If you truly mean 'do the _eigenvectors_ have to be real?', then not if 
>you allow A to operate on complex vectors.  If A is a real valued 
>symmetric matrix then it has a real valued eigenvalue, lambda, and a real 
>valued eigenvector, u which satisfy A * u = lambda * u.  If you allow A to 
>operate on complex vectors then i*u is a complex vector that satisfies 
>A*(i*u) = lambda*(i*u).

Thank you for the answer...
I mean eigenvectors are real.... but I agree that it was a real stupid 
question... As I usually work on p.s.d matrix, I am really suspicious with 
negative eigenvalues..

>< And what is the conditions to ensure that eigenvectors are real in the 
>case of an asymmetric matrix (if some conditions exist)?>
>
>Again, I assume you mean eigenvalues are real, not eigenvectors.  I don't 
>think there is any (useful) condition in general.  The eigenvalues are 
>real if det(A-lambda*I) has real roots.  Think of the case of a 2x2 matrix 
>where you can solve this by the quadratic equation and consider some examples.
>

Ok, I agree.. so it seems that no useful conditions exist on asymmetric 
matrices to be sure to obtain real eigenvalues..
St�phane DRAY
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