rlplot.egev: Return Level Plot for GEV Fits

Description

A return level plot is constructed for a GEV-type model.

Usage

rlplot.egev(object, plot.it = TRUE,
    probability = c((1:9)/100, (1:9)/10, 0.95, 0.99, 0.995, 0.999),
    add.arg = FALSE, xlab = "Return Period", ylab = "Return Level",
    main = "Return Level Plot",
    pch = par()$pch, pcol.arg = par()$col, pcex = par()$cex,
    llty.arg = par()$lty, lcol.arg = par()$col, llwd.arg = par()$lwd,
    slty.arg = par()$lty, scol.arg = par()$col, slwd.arg = par()$lwd,
    ylim = NULL, log = TRUE, CI = TRUE, epsilon = 1e-05, ...)

Arguments

object

A VGAM extremes model of the GEV-type, produced by vglm with a family function either "gev" or "egev".

plot.it

Logical. Plot it? If FALSE no plot will be done.

probability

Numeric vector of probabilities used.

add.arg

Logical. Add the plot to an existing plot?

xlab

Caption for the x-axis. See par.

ylab

Caption for the y-axis. See par.

main

Title of the plot. See title.

pch

Plotting character. See par.

pcol.arg

Color of the points. See the col argument of par.

pcex

Character expansion of the points. See the cex argument of par.

llty.arg

Line type. Line type. See the lty argument of par.

lcol.arg

Color of the lines. See the col argument of par.

llwd.arg

Line width. See the lwd argument of par.

slty.arg, scol.arg, slwd.arg

Correponding arguments for the lines used for the confidence intervals. Used only if CI=TRUE.

ylim

Limits for the y-axis. Numeric of length 2.

log

Logical. If TRUE then log="" otherwise log="x". This changes the labelling of the x-axis only.

Logical. Add in a 95 percent confidence interval?

epsilon

Numeric, close to zero. Used for the finite-difference approximation to the first derivatives with respect to each parameter. If too small, numerical problems will occur.

...

Arguments passed into the plot function when setting up the entire plot. Useful arguments here include sub and las.

Value

In the post slot of the object is a list called rlplot with list components
yp-log(probability), which is used on the x-axis.
zpvalues which are used for the y-axis
lower, upperlower and upper confidence limits for the 95 percent confidence intervals evaluated at the values of probability (if CI=TRUE).

Details

A return level plot plots $z_p$ versus $\log(y_p)$. It is linear if the shape parameter $\xi=0$. If $\xi<0$ then="" the="" plot="" is="" convex="" with="" asymptotic="" limit="" as="" $p$="" approaches="" zero="" at="" $\mu-\sigma="" \xi$.="" and="" if="" $\xi="">0$ then the plot is concave and has no finite bound. Here, $G(z_p) = 1-p$ where $0probability) and $G$ is the cumulative distribution function of the GEV distribution. The quantity $z_p$ is known as the return level associated with the return period $1/p$. For many applications, this means $z_p$ is exceeded by the annual maximum in any particular year with probability $p$.

The points in the plot are the actual data.

References

Coles, S. (2001) An Introduction to Statistical Modeling of Extreme Values. London: Springer-Verlag.

Examples

Run this code

gdata = data.frame(y = rgev(n <- 100, scale = 2, shape = -0.1))
fit = vglm(y ~ 1, egev, gdata, trace = TRUE)

# Identity link for all parameters:
fit2 = vglm(y ~ 1, egev(lshape = identity, lscale = identity,
                        iscale = 10), gdata, trace = TRUE)
coef(fit2, matrix = TRUE)
par(mfrow = c(1, 2))
rlplot(fit) -> i1
rlplot(fit2, pcol = "darkorange", lcol = "blue", log = FALSE,
       scol = "darkgreen", slty = "dashed", las = 1) -> i2
range(i2@post$rlplot$upper - i1@post$rlplot$upper) # Should be near 0
range(i2@post$rlplot$lower - i1@post$rlplot$lower) # Should be near 0

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