I need some help with a statistical design. I have two spatial point datasets: 1 is GPS points of known disease infections in a field (Yes or No Mark Variable). The other is potential detected infections by imagery.
The GPS points are all off by +/- 2m accuracy. However, I don't care. The GPS dataset pattern seems to match that of points detected from imagery- and I would like to statistically demonstrate this.
I am looking at a few methods, such as Monte Carlo, and maybe Ripley's K - in SpatStat. Can someone help to maybe get me started here? Are either of these designs going to be efficient for my needs?
Would love to get some help with the beginnings of a script.