Comparison of Monte Carlo simulations vs. covariance matrix. -- August 29, 2014 - 16:15

Hi Troels,

I really cannot follow and judge how the techniques compare.  I must
be getting old.  So to remedy this, I have created the
test_suite/shared_data/dispersion/Kjaergaard_et_al_2013/exp_error_analysis/
directory (r25437,
http://article.gmane.org/gmane.science.nmr.relax.scm/23187).  This
contains 3 scripts for comparing R2eff and I0 parameters for the 2
parameter exponential curve-fitting:

1)  A simple script to perform Monte Carlo simulation error analysis.
This is run with 10,000 simulations to act as the gold standard.

2)  A simple script to perform covariance matrix error analysis.

3)  A simple script to generate 2D Grace plots to visualise the
differences.  Now I can see how good the covariance matrix technique
is :)

Could you please check and see if I have used the
relax_disp.r2eff_err_estimate user function correctly?  The Grace
plots show that the error estimates are currently terrible.

Cheers,

Edward