bugNESSY - Bugs: bug #21885, The Monte Carlo simulation error...

 
 
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bug #21885: The Monte Carlo simulation error analysis is incorrect.

Submitted by:  Edward d Auvergne <bugman>
Submitted on:  Wed 02 Apr 2014 12:39:28 PM UTC  
 
Category: NESSY source codeSeverity: 5 - Blocker
Priority: 5 - NormalStatus: Postponed
Privacy: PublicAssigned to: None
Open/Closed: Open

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Wed 02 Apr 2014 12:39:28 PM UTC, original submission:

The Monte Carlo procedure for relaxation dispersion is as follows:

- Take the back calculated R2eff values from the fitted model.
- Randomise these X times with the original R2eff error. This assumes white noise, i.e. a Gaussian distribution.
- Fit the X data sets.
- The standard deviations for the X fitted parameters are the parameter error estimates.

However in NESSY, the implementation is not correct. See the file ./func/montecarlo.py, specifically line 122:

#create noisy dataset
for sim in range(0, len(x)):
y_sim.append(float(models[str(model)](x[sim], p_calculated)+uniform(-error, error)))

This uses the random.uniform() function, and the error is the standard deviation. However the R2eff values are not distributed as a uniform distribution with +/- 1 SD. They follow a normal or Gaussian distribution.

The result is that relaxation dispersion parameter errors are not correctly estimated.

Edward d Auvergne <bugman>
Project Administrator

 

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