GSI Forum
GSI Helmholtzzentrum für Schwerionenforschung

Home » PANDA » PandaRoot » Analysis » Covariance Matrices in RhoCandidates
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
occasional visitor
From: *customers.d1-online.com
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
 
Read Message
Read Message
Read Message
Read Message
Read Message
Read Message
Read Message
Read Message
Read Message
Read Message
Read Message
Read Message
Read Message
Read Message
Read Message
Read Message
Read Message
Read Message
Read Message
Read Message
Read Message
Previous Topic: option of polarization for Lambda-Lambdabar model
Next Topic: pi0 in fast simulation
Goto Forum:
  


Current Time: Sat Feb 16 13:03:17 CET 2019

Total time taken to generate the page: 0.03656 seconds