set.seed(9)
r <- raster(ncol=10, nrow=10)
r1 <- setValues(r, (1:ncell(r))/10 + rnorm(ncell(r)))
r2 <- setValues(r, (1:ncell(r))/10 + rnorm(ncell(r)))
r3 <- setValues(r, (1:ncell(r))/10 + rnorm(ncell(r)))
s <- stack(r1,r2,r3)
names(s) <- c('a', 'b', 'c')
xy <- cbind(rep(c(10,30,50), 3), rep(c(10,30,50), each=3))
refpt <- extract(s, xy)
ms <- mess(s, refpt, full=TRUE)
plot(ms)
## Not run:
# filename <- paste(system.file(package="dismo"), '/ex/bradypus.csv', sep='')
# bradypus <- read.table(filename, header=TRUE, sep=',')
# bradypus <- bradypus[,2:3]
# files <- list.files(path=paste(system.file(package="dismo"),'/ex', sep=''),
# pattern='grd', full.names=TRUE )
# predictors <- stack(files)
# predictors <- dropLayer(x=predictors,i=9)
# reference_points <- extract(predictors, bradypus)
# mss <- mess(x=predictors, v=reference_points, full=TRUE)
# plot(mss)
# ## End(Not run)
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