lmom (version 1.1)

evplot: Extreme-value plot

Description

evplot draws an ``extreme-value plot'', i.e. a quantile-quantile plot in which the horizontal axis is the quantile of an extreme-value type I (Gumbel) distribution. evdistp adds the cumulative distribution function of a distribution to an extreme-value plot. evdistq adds the quantile function of a distribution to an extreme-value plot. evpoints adds a set of data points to an extreme-value plot.

Usage

evplot(y, qfunc, para, npoints = 101, plim, xlim = c(-2, 5),
       ylim, type,
       xlab = expression("Reduced variate,  " * -log(-log(italic(F)))),
       ylab = "Quantile", rp.axis = TRUE, ...)

evdistp(pfunc, para, npoints = 101, ...)
evdistq(qfunc, para, npoints = 101, ...)

evpoints(y, ...)

Arguments of cumulative distribution functions and quantile functions

pfunc and qfunc can be either the standard Rform of cumulative distribution function or quantile function (i.e. for a distribution with $r$ parameters, the first argument is the variate $x$ or the probability $p$ and the next $r$ arguments are the parameters of the distribution) or the cdf... or qua... forms used throughout the lmom package (i.e. the first argument is the variate $x$ or probability $p$ and the second argument is a vector containing the parameter values).

Examples

# Extreme-value plot of Ozone from the airquality data
data(airquality)
evplot(airquality$Ozone)

# Fit a GEV distribution and add it to the plot
evdistq(quagev, pelgev(samlmu(airquality$Ozone)))

# Not too good -- try a kappa distribution instead
evdistq(quakap, pelkap(samlmu(airquality$Ozone)), col="red")