Timeline for Spatio-temporally cluster points per individual group using R
Current License: CC BY-SA 4.0
6 events
| when toggle format | what | by | license | comment | |
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| Jan 28, 2022 at 9:50 | comment | added | Spacedman | Code has to cope with anything :) In other words, you want to partition your data into a set X of subsets such that no point in subset A is within 2h of any point in subset B, or is within a space-time distance of (150m, 6day) of any point in subset B, for all pairs of subsets A,B in X (where A!=B). | |
| Jan 28, 2022 at 3:43 | comment | added | Ross | @Spacedman – Yes, by rule 1, those points would be grouped into one cluster. It's though very unlikely in a real-world scenario, since these data come from live large carnivores being tracked using GPS collars, and they shouldn't move such great distances within such short time spans. But, who knows, anything is possible I guess. | |
| Jan 27, 2022 at 22:24 | comment | added | Spacedman |
Ok, suppose your data has two spatial clusters 10km apart, on roughly the same hour. By rule 1 you'd group that into one cluster? I think what you've got here is really an adjacency construction using those thresholds as the adjacency condition. So I think its the same as constructing the NxN binary adjacency matrix and then using maybe igraph to get connected components from the corresponding graph....
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| Jan 27, 2022 at 16:45 | comment | added | Ross | @Spacedman – They could be done sequentially, but they don't have to be done separately I guess. I just tried to explain the rules in a clear way. | |
| Jan 27, 2022 at 13:54 | comment | added | Spacedman | I don't understand the two steps. Are they done sequentially? So Step 1 you could be clustering two points at any distance, and then Step 2 you do an essentially 3d clustering with spatial=150, time=6 distance, and you could end up with a "cluster" that's separated spatially by any distance because of step 1? | |
| Jan 27, 2022 at 8:50 | history | asked | Ross | CC BY-SA 4.0 |