Empirical beyesian kriging Regression prediction

[kaoutarbouziane]

hello ,

I m trying to model some pollutant air concentration ,so I used the the new added interpolation method Empirical beyesian kriging Regression prediction from Arcgis pro,after setting the model characteristics I got a map wish I found acceptable but still I need second opinion about fitted semivariogram because NOT all the points  fall in the middle of the semivariogram spectrum.I tried all the transformation and the semivagiogram types and the best result (please see attached)  for the fitted semivagiogram was found when I used :log empirical transformation and ,K-bessel semivariogram type.

so my question is do you think this is acceptable results to use (see attached results)? because  I couldn't find any literature in esri website  about how to interpret the nugget and partial still and range for the Empirical beyesian kriging Regression prediction since it  creates a large number of semivariograms for each subset.

[DanPatterson_Retired]

Steve Lynch‌ has more experience in this area.

I have flagged him

[EricKrause · Accepted solution]

Hi Kaoutar,

I see in the image that you only have 11 input points.  I would not recommend that you attempt to use such a complicated model on such a small number of points.  None of the graphs are particularly meaningful when your kriging model has nearly as many parameters as input points.

Sorry for the bad news, but if you absolutely need to interpolate these points, you should use something very simple, such as Global Polynomial Interpolation or IDW.

-Eric

[kaoutarbouziane]

thank you for your help it was useful