quant: Plot of GPD Tail Estimate of a High Quantile

In evir: Extreme Values in R

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

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

gpd, plot.gpd, gpd.q, shape

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 

Example output

evir documentation built on May 2, 2019, 6:11 p.m.