rlplot {extRemes} | R Documentation |
Plots several return levels against the return period for a fitted object from one of
the ismev functions: gev.fit
and gpd.fit
.
rlplot(z, ci = 0.05, add.ci = FALSE)
z |
A list object as returned by one of gev.fit or gpd.fit (with appropriate class attribute added). |
ci |
The (1-ci)*100 confidence value. |
add.ci |
logical if true will add confidence bounds to plot. |
Given a fitted list object from gev.fit
or gpd.fit
–attributed with the class
"gev.fit" or "gpd.fit", respectively–the return level plot is generated. Confidence bounds,
if included, are found by the delta method, which is generally appropriate for shorter return
periods, but not for longer return periods because the return level distribution is generally
skewed. Therefore, if a plot with better estimates of the confidence bounds are desired, use
add.ci=FALSE
, and use the R function lines
to add different bounds (e.g., using
values obtained from the gev.parameterCI
or gpd.parameterCI
functions).
This function is simply a modification of Stuart Coles' functions gpd.rl
and gev.rl
(Coles, 2001).
A plot is created. If assigned to an object, a list will be returned with the following items.
period |
The return periods used for calculating the return levels. |
level |
The estimated return level for each return period. |
lower |
If add.ci is TRUE, then this is a vector of lower 1-ci confidence bounds. Otherwise the value is NULL. |
upper |
If add.ci is TRUE, then this is a vector of upper 1-ci confidence bounds. Otherwise the value is NULL. |
Eric Gilleland
Coles, Stuart. "An introduction to statistical modeling of extreme values", Springer-Verlag (London), 2001.
Gilleland, Eric and Katz, Richard W. Tutorial for the 'Extremes Toolkit: Weather and Climate Applications of Extreme Value Statistics.' http://www.assessment.ucar.edu/toolkit, 2005.
gev.parameterCI
, gpd.parameterCI
, gev.diag
, gpd.diag
data(ftcanmax) fit <- gev.fit( ftcanmax[,"Prec"]) class( fit) <- "gev.fit" rlplot( fit)