library(evmix)
set.seed(0)
x = rnorm(1000)

# Fit normal bulk model with GPD for upper tail
fit = fnormgpd(x)

# plot fit over sample density histogram
xx = seq(-5, 5, 0.01)
hist(x, breaks = 100, freq = FALSE)
with(fit, lines(xx, dnormgpd(xx, nmean, nsd, u, sigmau, xi), col="blue"))
abline(v = fit$u, col="blue")

# Add constraint of continuous density at threshold
fitcon = fnormgpdcon(x)

with(fitcon, lines(xx, dnormgpdcon(xx, nmean, nsd, u, xi), col="red"))
abline(v = fitcon$u, col="red")

help(evmix)

# Nonparametric bulk fit
fitkde = fkdengpd(x)

with(fitkde, lines(xx, dkdengpd(xx, x, lambda, u, sigmau, xi), col="green"))
abline(v = fitkde$u, col="green")

# Usual model diagnostics default to focus on upper tail
evmix.diag(fit)

# Can see entire fit
evmix.diag(fit, upperfocus=FALSE)

# Usual MRL plot with some extra features
data(FtCoPrec,package="extRemes")
mrlplot(FtCoPrec[,5], try.thresh=c(0.395, 0.8, 1.2))