Description
Mapping Averaged Pairwise Information.
Description
Mapping Averaged Pairwise Information (MAPI) is an exploratory method providing graphical representations summarizing the spatial variation of pairwise metrics (eg. distance, similarity coefficient, ...) computed between georeferenced samples.
README.md
mapi
MAPI is an exploratory method providing graphical representations of the spatial variation of pairwise metrics (eg. distance, similarity coefficient, ...) computed between georeferenced samples.
Installation
You can install the released version of mapi from CRAN with:
install.packages("mapi")
Example
This basic example illustrates MAPI usage based on internal data. This dataset have been generated by simulation. In real life, the crs 3857 is not accurate. Use a projection of coordinates in line with your sampling area. For demonstration purposes 100 permutations are faster but unreliable. For a true dataset 1000 to 10,000 permutations should be OK.
library(mapi)
data("samples")
data(metric)
mapi.out <- MAPI_RunAuto(samples, metric, crs=3857, beta=0.5, nbPermuts=100)
mapi.tails <- MAPI_Tails(mapi.out, alpha=0.05)
MAPI_Plot2(mapi.out, mapi.tails, samples=samples)