[timeDomain: model for Time series] discussion on Timeseries Data model Note / ND-point .... or not ??? !!!
CresitelloDittmar, Mark
mdittmar at cfa.harvard.edu
Tue Sep 12 16:47:22 CEST 2017
Just one remark.. on the "Observable"
On Sun, Sep 3, 2017 at 8:48 AM, Jiří Nádvorník <nadvornik.ji at gmail.com>
wrote:
>
> 2) Errors
>
> The Observables in the cube model are STC CoordMeasure instances, which
> include the measured value, associated error, and frame reference. The
> error modeling to date is assuming a 1-1 association of the value to its
> error (eg Value +/- Error ). The modeling of errors in STC2 is very
> extensible and targets the most common error types. It is very compatible
> to have a separate effort take place to model other sorts of errors (
> statistical distributions ) and extend the base STC-2 error class.
>
> *[[Jiri Nadvornik]] I agree that the Error class in STC2 is very
> extensible, but I would go even one step further here because when we have
> „statistical distribution“ for Error, what’s the Value then? I’d suppose it
> is just some Expectation or Mean value, which is already part of that
> statistical distribution.*
>
>
> If the relation is a bit more broad, and the 'measure' itself is a
> statistical distribution kind of thing, then what you are describing is not
> an Observable. This sort of thing I expected might come up with simulated
> data (when we think about bringing SimDM and Cube more in line with each
> other.. (they are quite compatible)). If this is the case, we we should
> define a different kind of DataAxis which better facilitates the
> statistical/mathematical nature of the measurement.
>
> *[[Jiri Nadvornik]] I don’t agree completely on the first statement here –
> I think that even an Observable ‚measure‘ can be represented with a
> statistical distribution. Typically, a point spread function will have a
> gaussian distribution where the Flux Value+Error would be just Mean+Sigma
> of that statistical distribution.*
>
>
by "is not an Observable", I didn't mean that it was not conceptually an
observable entity (like Flux), I meant that it wasn't the thing I labeled
'Observable' in the cube diagram. More specifically, I think that there
would be a branch somewhere in that line (either at 'Observable' or
'CoordMeasure' ) where a different type of value is defined which better
models a statistical distribution rather than a measured value+error.
We could address this more directly with an example.
Mark
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