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Positive Definite Matrix

On Sat, 29 Jan 2011, David Winsemius wrote:

            
But again, that is not usually what you want.  There is no guarantee 
that the result is positive-definite enough that the Cholesky 
decomposition will work.  Give up on Cholesky factors unless you have 
a matrix you know must be symmetric and strictly positive definite, 
and use the eigendecomposition instead (setting negative eigenvalues 
to zero).  You can then work with the factorization to ensure that 
(for example) variances are always non-negative because they are 
always computed as sums of squares.

This sort of thing is done in many of the multivariate analysis 
calculations in R (e.g. cmdscale) and in well-designed packages.