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)
}