Timeline for Values of ordinary kriging with gstat and terra are equal as the input data
Current License: CC BY-SA 4.0
5 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Feb 19 at 12:35 | vote | accept | msug | ||
| Feb 17 at 8:41 | comment | added | Spacedman | There's nothing to stop you using your grid of inputs to predict via kriging at a different set of grid points, for example something with 25 cells for every cell of your input grid. In this case you'll still get identical predictions if your new points coincide with the input points. It all depends on what you are trying to learn from your data. | |
| Feb 17 at 8:39 | comment | added | Spacedman | Kriging is used to estimate values where you don't have data. If you have data on the grid locations, then predicting at the grid locations will return the input values. There's no point predicting values on your grid because you already know the ground truth, and kriging returns that. Removing a zero would be sensible if the zero meant "no measurement taken here" and you want to know what the value would have been if a measurement had been taken. If a 0 was truly recorded here, you leave it in and kriging predicts zero at that location. | |
| Feb 17 at 5:18 | comment | added | msug | Thanks for the input. So in theory if I would like to predict values in my grid using kriging I should erase the entries I'd like to interpolate? For example the 0's in my data frame? It does not sound like the right thing to do, I think. Which method could I use to interpolate the values I have? | |
| Feb 16 at 23:51 | history | answered | Spacedman | CC BY-SA 4.0 |