This content has been marked as final.
Show 12 replies

Re: Best interpolation methods
EKrauseesristaff Feb 15, 2012 1:18 PM (in response to maya3m)Most parameters apply only for that particular interpolator. The Power in IDW, for example, has no analogous parameter in any other interpolators.
Global Polynomial Interpolation, Local Polynomial Interpolation, and Kernel Smoothing are all based on polynomials, so the Order of Polynomial means the same thing in each tool. Additionally, LPI and KS share Kernel types because they're based on local kernels.
The only parameters that are shared across the board are related to the searching neighborhood (except when you introduce barriers).
The domain of each parameter depends on what the parameter does (for example, the range in kriging has to be greater than 0). These domains are all documented, and if you try to use a value outside that domain, the software will throw an error telling you that it is outside the parameter domain.
You should always consider trend removal and transformations, but that doesn't mean you have to use them. Only use them if they help create a better model (which you can judge with crossvalidation statistics). 
Re: Best interpolation methods
maya3m Feb 17, 2012 9:24 AM (in response to maya3m)Thank you
I would like to know whether there is any specific range for RBF interpolations?
Because when i did my work, i obtained a default parameter as 30.262 for completely regularised spline, 43.588 for spline with tension and 1E20 for tension spline. Can i continue my work with these default parameters? Is this the right way?
To find the best interpolation methods, is it the way that i change the parameters for one type of interpolation method and find the best model from it and again find best models for other methods by changing their corresponding parameters.
For my work , is it necessary to create test data and training data and then do the analysis to get the best model? 
Re: Best interpolation methods
EKrauseesristaff Feb 17, 2012 10:18 AM (in response to maya3m)The default Kernel Parameter in RBF is calculated such that it minimizes the RootMeanSquare error (RMS) during crossvalidation. Comparing the RMS values from different models is the most common method of deciding which model is better. Comparing crossvalidation statistics between models can get complicated, but the ruleofthumb is to use the model with the lowest RMS. All interpolation methods will calculate RMS during crossvalidation, and it has the same meaning for all interpolators, so it can be compared across the board to decide which interpolation method (and which parameters) to use.
Theoretically, the kernel parameter can take any real number, but computer limitations keep the possible range between +/ 1.79769 x 10^308. 
Re: Best interpolation methods
maya3m Feb 19, 2012 6:55 PM (in response to maya3m)Thank You So Much
While i did ESDA, with the temperature data , in the Histogram tool i observed that my data is not normally distributed and when i did transformations I couldnt find any change. Why is it like that?
Was my data normally distributed? But it didnt show a bell shaped graph that appear for a normal distribution. I am attaching the screen shots of histogram and QQ plot result please check and help me
ESDAdoubt.docx 120.3 K


Re: Best interpolation methods
EKrauseesristaff Feb 20, 2012 6:02 AM (in response to maya3m)From that Word doc, it doesn't look like a Log transformation is a good choice. Instead, try a Normal Score Transformation. In the Geostatistical Wizard, use Kriging, then on the second page, use "Simple" as the kriging type. The default transformation will be "Normal Score." Click Next. On this screen, change "Type" to Gaussian Kernels. See if the default fit seems to fit your histogram. You may need to try changing the number of kernels if the default fit doesn't look good. If you find a transformation that fits your histogram, the software will automatically do the backtransformation for you, so the result of the kriging will be in the original units (not transformed units).
The Normal Score transformation is the most powerful and functional transformation, but it's only available for Simple, Probability, and Disjunctive kriging. 
Re: Best interpolation methods
maya3m Feb 20, 2012 6:57 AM (in response to maya3m)Thank you
But if i want to any do any other kriging other than simple and disjunctive , can i assume the histogram data as normal as obtained in the wordWill there be any wrong with this? Is this assumption correct? 
Re: Best interpolation methods
EKrauseesristaff Feb 20, 2012 7:05 AM (in response to maya3m)The histogram and QQ plot look pretty good without a transformation; you'll probably be fine without one. That being said, I would still try Simple Kriging with a Normal Score Transformation. 
Re: Best interpolation methods
maya3m Feb 20, 2012 6:28 PM (in response to maya3m)Thank you so much for the reply 
Re: Best interpolation methods
maya3m Feb 22, 2012 7:25 PM (in response to maya3m)What is the real difference between Completely regularized spline, spline with tension and thin plate spline?
How can we say that in RBF, the point Surface created must go through each measured sample value and also it predicts values above the maximum and below the minimum measured values 
Re: Best interpolation methods
slynchesristaff Feb 23, 2012 7:59 AM (in response to maya3m)Have you looked in the help?
http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#//00310000002p000000.htm
If you want additional information on splines I would suggest doing a literature search.
Regards
Steve 
Re: Best interpolation methods
maya3m Aug 10, 2012 4:10 AM (in response to maya3m)Respected sir,
Even though i read ESRI help regarding RBF functions: Completely regularized spline, spline with tension and thin plate spline i couldnot make out the differences between the three. Can you please help me with this ? I read that all these provide similar output surfaces then how can the user define these? 
Re: Best interpolation methods
slynchesristaff Aug 10, 2012 8:06 AM (in response to maya3m)While doing a search did you find
http://resources.arcgis.com/en/help/main/10.1/index.html#//009z00000078000000 ?
Have you looked at the 2 references ?
Regards
Steve