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.

1 2 |

`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 |

For every model `gpd`

is called. Evaluation may be slow.
Confidence intervals by the Wald method (which is fastest).

A table of results is returned invisibly.

`gpd`

, `plot.gpd`

,
`gpd.q`

, `shape`

1 2 3 4 | ```
## 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
``` |

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