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

This function compute estimate of high quantile or value-at-risk (VAR) using mean of order p (MOP) method.

1 |

`x` |
Data vector. |

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

`p` |
a vector of mean order. |

`q` |
quantile level. |

`method` |
Method used, ("MOP", default) and reduced-bias MOP ("RBMOP"). |

For heavy tails, Gomes et al. (2013) introduces a new class of high quantile estimators based on a class of mean of order p (MOP) extreme value index (EVI) estimators is givin by

*Q(k) = (X_{n-k:n}) (k/nq)^{H_p(k)},*

where *H_p(k)* is MOP EVI estimator and *X_{i:n}* is order statistic.

a matrix of EVI and VaR estimates, corresponds to `k`

row and `p`

columns. When `Method = "RBMOP"`

shape and scale second order parameters estimates are also returned.

B G Manjunath [email protected]

Brilhante, M.F., Gomes, M.I. and Pestana, D. (2013). A simple generalisation of the Hill estimator.
*Computational Statistics and Data Analysis*, **57**, 518– 535.

Beran, J., Schell, D. and Stehlik, M. (2013). The harmonic moment tail index estimator: asymptotic distribution and robustness. *Ann Inst Stat Math*, Published Online.

Gomes, M.I., Brilhante, M.F. and Pestana, D. (2013). New reduced-bias estimators of a positive extreme value index. *Submitted article*.

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

1 2 3 4 5 |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.