quant: Plot of GPD Tail Estimate of a High Quantile
Description
Creates a plot showing how the estimate of a high quantile in
the tail of a dataset based on the GPD approximation varies with
threshold or number of extremes.
Usage
quant(data, p = 0.99, models = 30, start = 15, end = 500, reverse =
TRUE, ci = 0.95, auto.scale = TRUE, labels = TRUE, …)
Arguments
data
numeric vector of data
p
desired probability for quantile estimate (e.g. 0.99
gives 99th percentile)
models
number of consecutive gpd models to be fitted
start
lowest number of exceedances to be considered
end
maximum number of exceedances to be considered
reverse
should plot be by increasing threshold
(TRUE) or number of extremes (FALSE)
ci
probability for asymptotic confidence band; for no
confidence band set to zero
auto.scale
whether or not plot should be automatically scaled;
if not, xlim and ylim graphical parameters may be entered
labels
whether or not axes should be labelled
…
other graphics parameters
Value
A table of results is returned invisibly.
Details
For every model gpd is called. Evaluation may be slow.
Confidence intervals by the Wald method (which is fastest).
# NOT RUN {data(danish)
# }# NOT RUN {quant(danish, 0.999)
# }# NOT RUN {# Estimates of the 99.9th percentile of the Danish losses using # the GPD model with various thresholds # }