URL:
<http://gna.org/task/?7882>
Summary: Implement Monte-Carlo simulation, where errors are
generated with width of standard deviation or residuals
Project: relax
Submitted by: tlinnet
Submitted on: Fri 16 Jan 2015 04:14:30 PM UTC
Should Start On: Fri 16 Jan 2015 12:00:00 AM UTC
Should be Finished on: Fri 16 Jan 2015 12:00:00 AM UTC
Category: relax's source code
Priority: 5 - Normal
Status: In Progress
Percent Complete: 0%
Assigned to: tlinnet
Open/Closed: Open
Discussion Lock: Any
Effort: 0.00
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Details:
This is implemented due to strange results.
A relaxation dispersion on data with 61 spins, and a monte carlo simulation
with 500 steps, showed un-expected low errors.
-------
results.read(file=fname_results, dir=dir_results)
# Number of MC
mc_nr = 500
monte_carlo.setup(number=mc_nr)
monte_carlo.create_data()
monte_carlo.initial_values()
minimise.execute(min_algor='simplex', func_tol=1e-25, max_iter=int(1e7),
constraints=True)
monte_carlo.error_analysis()
--------
The kex was 2111 and with error 16.6.
When performing a dx.map, some weird results was found:
i_sort dw_sort pA_sort kex_sort chi2_sort
471 4.50000 0.99375 2125.00000 4664.31083
470 4.50000 0.99375 1750.00000 4665.23872
So, even a small change with chi2, should reflect a larger
deviation with kex.
It seems, that change of R2eff values according to their errors, is not
"enough".
According to the regression book of Graphpad
http://www.graphpad.com/faq/file/Prism4RegressionBook.pdf
Page 33, and 104.
Standard deviation of residuals is:
Sxy = sqrt(SS/(N-p))
where SS is sum of squares. N - p, is the number of degrees of freedom.
In relax, SS is spin.chi2, and is weighted.
The random scatter to each R2eff point should be drawn from a gaussian
distribution with a mean of Zero and SD equal to Sxy.
Additional, find the 2.5 and 97.5 percentile for each parameter.
The range between these values is the confidence interval.
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File Attachments:
-------------------------------------------------------
Date: Fri 16 Jan 2015 04:14:30 PM UTC Name: Screenshot-1.png Size: 161kB
By: tlinnet
<http://gna.org/task/download.php?file_id=23527>
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[task #7882] Implement Monte-Carlo simulation, where errors are generated with width of standard deviation or residuals