## Fix a 8-dimensional asymmetric tail dependence structure
ds8 <- gen.ds(d = 8)
## Generate a 200-sample of Frechet margins Mevlog model associated with ds8
sample8 <- rMevlog(n = 200 , ds = ds8)
## Plot the tail dependograph of ds8
graphs(ds = ds8)
## Its empirical version for k = 20
graphsEmp(sample = sample8, k = 20)
## Its empirical version for k = 20 restricted to the 3 largest edges
graphsEmp(sample = sample8, k = 20, select = 3)
## Plot the Inverse extremal coefficients graph of ds8
graphs(ds = ds8, which = "iecgraph")
## Its empirical version for k = 20
graphsEmp(sample = sample8, k = 20, which = "iecgraph")
## Its empirical version for k = 20 restricted to the 3 largest edges
graphsEmp(sample = sample8, k = 20, which = "iecgraph", select = 3)
## Plot the empirical tail dependograph
## on river discharge data for tributaries
## of the Danube extracted from
## Asadi P., Davison A.C., Engelke S. (2015).
## “Extremes on river networks.”
## The Annals of Applied Statistics, 9(4), 2023 – 2050.
#NOT RUN dan <- graphicalExtremes::danube$data_clustered
#NOT loc <- as.matrix(graphicalExtremes::danube$info[,c('PlotCoordX', 'PlotCoordY')])
#NOT graphsEmp(dan, k=50, layout = loc)
Run the code above in your browser using DataLab