Hi, The covariance matrix error estimate is not so bad and it should be close to the MC simulations in most cases. But MC simulations are almost always of higher quality and do not suffer from artefacts. Regards, Edward On 28 August 2014 09:46, <tlinnet@xxxxxxxxxxxxx> wrote:
Author: tlinnet Date: Thu Aug 28 09:46:45 2014 New Revision: 25364 URL: http://svn.gna.org/viewcvs/relax?rev=25364&view=rev Log: Added a warning to the auto analyses about error estimation from the Co-variance. task #7822(https://gna.org/task/index.php?7822): Implement user function to estimate R2eff and associated errors for exponential curve fitting. Modified: trunk/auto_analyses/relax_disp.py Modified: trunk/auto_analyses/relax_disp.py URL: http://svn.gna.org/viewcvs/relax/trunk/auto_analyses/relax_disp.py?rev=25364&r1=25363&r2=25364&view=diff ============================================================================== --- trunk/auto_analyses/relax_disp.py (original) +++ trunk/auto_analyses/relax_disp.py Thu Aug 28 09:46:45 2014 @@ -512,6 +512,10 @@ # Print subsection(file=sys.stdout, text="Estimating errors from Covariance matrix", prespace=1) + # Raise warning. + text = 'Estimating errors from the Covariance matrix is highly likely to "quite" wrong. Use only with extreme care, and for initial rapid testing of your data.' + warn(RelaxWarning(text)) + # Estimate errors self.interpreter.relax_disp.r2eff_err_estimate() else: _______________________________________________ relax (http://www.nmr-relax.com) This is the relax-commits mailing list relax-commits@xxxxxxx To unsubscribe from this list, get a password reminder, or change your subscription options, visit the list information page at https://mail.gna.org/listinfo/relax-commits