A return level plot is constructed for a GEV-type model.
rlplot.gevff(object, show.plot = TRUE,
probability = c((1:9)/100, (1:9)/10, 0.95, 0.99, 0.995, 0.999),
add.arg = FALSE, xlab = if(log.arg) "Return Period (log-scale)" else
"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.arg = TRUE, CI = TRUE, epsilon = 1e-05, ...)
In the post
slot of the object is a list called
rlplot
with list components
-log(probability)
, which is used on the x-axis.
values which are used for the y-axis
lower and upper confidence limits for the
95 percent confidence intervals evaluated at the values of
probability
(if CI=TRUE
).
A VGAM extremes model of the
GEV-type, produced by vglm
with a family function either
"gev"
or "gevff"
.
Logical. Plot it? If FALSE
no plot will be done.
Numeric vector of probabilities used.
Logical. Add the plot to an existing plot?
Caption for the x-axis. See par
.
Caption for the y-axis. See par
.
Title of the plot. See title
.
Plotting character. See par
.
Color of the points.
See the col
argument of par
.
Character expansion of the points.
See the cex
argument of par
.
Line type. Line type.
See the lty
argument of par
.
Color of the lines.
See the col
argument of par
.
Line width.
See the lwd
argument of par
.
Correponding arguments for the lines used for the
confidence intervals. Used only if CI=TRUE
.
Limits for the y-axis. Numeric of length 2.
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?
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
.
T. W. Yee
A return level plot plots probability
)
and
The points in the plot are the actual data.
Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values. London: Springer-Verlag.
gevff
.
gdata <- data.frame(y = rgev(n <- 100, scale = 2, shape = -0.1))
fit <- vglm(y ~ 1, gevff, data = gdata, trace = TRUE)
# Identity link for all parameters:
fit2 <- vglm(y ~ 1, gevff(lshape = identitylink, lscale = identitylink,
iscale = 10), data = gdata, trace = TRUE)
coef(fit2, matrix = TRUE)
if (FALSE) {
par(mfrow = c(1, 2))
rlplot(fit) -> i1
rlplot(fit2, pcol = "darkorange", lcol = "blue", log.arg = 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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