Concept of model validation and outlier detection in JAG3D (Software)

Micha ⌂, Bad Vilbel, Mittwoch, 12. April 2017, 18:43 (vor 14 Tagen) @ E_merlet


Ok, and do I have to extend the model with \nabla by myself or does the software do it by itself?

JAG3D estimates in the last iteration step and shows the results in one of the columns of the observation tables.

So, it means there is always an error, for every observation.

There is in most cases a discrepance to zero, yes. But remember, your measurement process is not perfect and some kind of noise influences your observation. Thus, can be an error.

The stochastic test tells us if the error is too big and has to be corrected or not. Right?

With an specific probability value, yes.

∇ ≠ 0 means the observation is an outlier. Does it not mean it has to be removed

... or correcting or something else - but yes, you have to handle dubios observations and gives you a hint about the size of the possible outlier.

So, B is like the jacobian matrix A

Yes. In the extended model, B is a part of the extended A, i.e. A := [A B].

And what is E

E represents the identity matrix.


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JAG3D, Stochastic test, Outlier

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