rm(list=ls())
library(SpatialExtremes)
data(rainfall)
## We are going to plot a bunch of circle centered at weather
## stations, whose radius is proportional to the deviation from the
## areal mean of the gev parameters and whose color is blue or red
## depending if we're below or above the areal mean
## This is similar with what we've done in SpatialTrends.R but with
## each GEV parameters, i.e., location, scale and shape---thus 3 plots
## Fit a generalized extreme value distribution at each location
gev.mles <- apply(rain, 2, gevmle) ## <<-- if you don't understand this line please ask
par(mfrow = c(1, 3)) ## <<-- divide the graphic window in a (1 x 3) matrix
norm.factor <- c(0.5, 2, 50)
for (i in 1:3){
## Plot Switzerland usign an existing function---always a good idea to
## start with that
swiss(city = TRUE)
## Do actually the symbol plot
areal.mean <- mean(gev.mles[i,])
col <- c("red", "blue")[2 - (gev.mles[i,] >= areal.mean)]
radius <- norm.factor[i] * abs(gev.mles[i,] - areal.mean)
symbols(coord[,-3], circles = radius, inches = FALSE, add = TRUE,
bg = col)
}