In sci.stat.consult Rich Ulrich <[EMAIL PROTECTED]> wrote:

>> 
>   [ snip - redundant questioning ]

> Any covariance matrix computed on full data is assured to be
> non-negative definite.


  That's the underlying theorem I was missing.  I have
  to go try to prove it now.

  (I was thinking sampling fluctuation might once in a while
  bring up some sample matrices that violate this constraint, 
  but I guess by analogy with sample univariate variances
  it can't happen.  The proof isn't as easy for the matrix case)


  Thanks
   Ron
.
.
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