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Dear Eric Many thanks for the reply. I had no idea it was such a complicated question, and that probably says volumes about my lack of knowledge 🙂 Thank you for the short answer. At least I know not to pursue that avenue anymore. All the best Stephen
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05-15-2012
01:39 PM
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Hi Please forgive me if this is a beginner's question, but I am a beginner 🙂 I have a kriging model of rainfall for an area. For each point rainfall station I have a rainfall total and elevation. Unfortunately, the root mean squared error is not very good - it's around 13. I wanted to know about different ways to improve my model and reduce the rmse. I have read that the residuals of kriging (i.e. the actual minus predicted values) for each rainfall station can be themselves kriged and the results of this added back to the original model to improve prediction quality. So my questions are: 1. Is this a valid approach to improving a model, and if so, why? 2. If this is a valid approach, can you provide a quick step by step description of how to add the residual kriging results back to the original kriging model? 3. Do you have any other suggestions for techniques which I could use to improve my kriging results? Note that I also have elevation data, but co-kriging with this hardly seems to improve the model. I hope this is a sensible question. Many thanks for all your help Stephen Vitoria
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05-14-2012
01:28 PM
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Dear Eric Many thanks for all your help, and for the advice. Is it therefore true to say that when evaluating actual versus predicted differences (i.e. errors in prediction), that I should be using the "GA Layer to Points" values and not the values produced by the Geostatistical Wizard, because the "GA Layer to Points" values are based on the complete model and not the n-1 model? Thanks for the advice regarding splitting the data in half and comparing the results from each half to each other. Do you happen to have any links that you could post (possibly to blogs, etc...) that explain this in more detail, or indeed to any articles that might help me improve kriging modelling (I'm a beginner). Thanks again for such a quick reply Stephen
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05-10-2012
05:42 AM
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Hi I perform ordinary kriging (or co-kriging) on a dataset and in the final cross validation step of the geostatistical wizard, I can see a table which shows actual vs predicted values for each point in the dataset. When I finish the geostatistical wizard, I create a prediction surface which is added as a layer to my project. I can then right click on the prediction layer and select the "Validation/Prediction" option which opens up the "GA Layer to Points" tool. I select the input dataset and the field which I had originally performed kriging on. This creates a new shape file which I can add to my project. When I examine the attribute table for the new layer that I have just created using the "Validation/Prediction" option, it also shows actual and predicted values for each point in the data set. However, the predicted values are substantially different from those that were shown in the final cross validation screen of the geostatistical wizard. Can anyone tell me why they are different, and which cross validation table is correct? I don't understand 😞 Many thanks for all your help Stephen Vitoria
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05-09-2012
01:01 PM
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