quant function

Plot of GPD Tail Estimate of a High Quantile

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.

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

Returns

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).

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