Description Usage Arguments Details Value Author(s) References See Also Examples

This function computes high quantile or value-at-risk (VaR) estimate based on peaks over random threshold (PORT) Hill extreme value index (EVI) estimate.

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`x` |
Data vector. |

`k` |
a vector of number of upper order statistics. |

`q1` |
quantile for PORT. |

`q2` |
quantile level. |

`method` |
Method used, ("PMOP", default) and reduced-bias PMOP ("PRBMOP"). |

The computation of the high quantile estimate is based on the work by Gomes et al. (2006).

a `k`

dimensional vector of PORT Hill and high quantile estimates. When `Method = "RBMOP"`

shape and scale second order parameters estimates are also returned.

B G Manjunath [email protected]

Araujo Santos, P., Fraga Alves, M.I. and Gomes, M.I. (2006). Peaks over random threshold methodology for tail index and quantile estimation.
*Revstat*, **4**(3), 227–247.

Gomes, M.I., Figueiredo, F., Henriques-Rodrigues, L. and Miranda, M.C. (2006). A quasi-PORT methodology for VaR based on second-order reduced-bias estimation.

Weissman, I. (1978). Estimation of parameters and large quantiles based on the k largest observations. *J. Amer. Statist. Assoc.*, **73**, 812– 815.

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