Timeline for Kriging: extract data for other unknown points
Current License: CC BY-SA 4.0
6 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Apr 4, 2023 at 8:54 | vote | accept | Elena Iakimova | ||
| Apr 3, 2023 at 19:46 | comment | added | Elena Iakimova | Yes, I'm only interested in one point of "cava" per month. It seems to work, make it up right? | |
| Apr 3, 2023 at 19:43 | comment | added | Spacedman | Not knowing what locations you wanted to predict at I made a most general example. Does that code you posted in the comment above do the equivalent of what you want to do with your data using the sample data? | |
| Apr 3, 2023 at 19:31 | comment | added | Elena Iakimova |
cava <- data.frame(Lon = 16.44529, Lat = 39.495616) coordinates(cava) <- ~Lon+Lat proj4string(cava) <- proj4string(dataObj) times <- seq(as.POSIXct("2021-07-01 00:00:00 UGT"), as.POSIXct("2021-07-31 00:00:00 UGT"), length.out=31) stpts = STF(cava, sort(as.POSIXct(times))) pts_kriged <- krigeST(values~1, data=dataObj, newdata=stpts, modelList=metricFit, computeVar=TRUE) pts_kriged
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| Apr 3, 2023 at 19:28 | comment | added | Elena Iakimova | I couldn't understand the phrase "I'll create 10 random points at the three time points in the data". Finding values at one point per month is what I am interested in. | |
| Apr 3, 2023 at 16:15 | history | answered | Spacedman | CC BY-SA 4.0 |