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Re: Covariance Matrices in RhoCandidates [message #16344 is a reply to message #16343] Wed, 16 April 2014 19:37 Go to previous messageGo to previous message
SHenssler is currently offline  SHenssler
Messages: 13
Registered: March 2014
Location: FZ Jülich
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Hello Stefano,

positive semi definite does not mean that there cannot be negative values.
The Definition says, that any vector y multiplied in the way: y^t * C * y,
where C is the Covariance Matrix, must result in a value greater or equal to zero.
In a way that is the proof, that the Chi-Square value ( y^t * C^-1 * y ) is always positive.
Or rather, if C is not positive semi definite, then it cannot ne guaranteed that the Chi Square value is positive.
It is a mathematical property that every Covarince Matrix Must have.

Cheers
Simon
 
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