quant {evir} | R Documentation |
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
( |
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 |
Details
For every model gpd
is called. Evaluation may be slow.
Confidence intervals by the Wald method (which is fastest).
Value
A table of results is returned invisibly.
See Also
Examples
## Not run: data(danish)
## Not run: quant(danish, 0.999)
# Estimates of the 99.9th percentile of the Danish losses using
# the GPD model with various thresholds