Description Usage Arguments Details Value Author(s) References Examples

This function computes empirical-likelihood based estimators for the angular distribution function of a bivariate extreme value distribution.

1 2 |

`Y` |
data frame with two columns from which the estimate is to be computed. |

`tau` |
value used to threshold the data; by default it is set as the 0.95 quantile of the pseudo-radius. |

`nu` |
concentration parameter of beta distribution which controls the amount of smoothing. |

`grid` |
grid with coordinates of the points where the angular
density is estimated; by default |

`method` |
a character string setting the method to be used. By
default |

`raw` |
logical; if |

The smooth angular density was introduced in by de Carvalho et al
(2013). `method = "euclidean"`

implements the version of the
method based on Euclidean likelihood weights, whereas ```
method =
"empirical"
```

uses Empirical likelihood weights.

`h` |
the estimate angular density values. |

`grid` |
grid with coordinates of the points where the angular density is estimated. |

`w` |
pseudo-angles. |

`nu` |
concentration parameter of the Beta-kernel. |

`Y` |
raw data. |

The `plot`

method depicts the smooth angular density.

Miguel de Carvalho

de Carvalho, M., Oumow, B., Segers, J. and Warchol, M. (2013) A
Euclidean likelihood estimator for bivariate tail dependence.
*Communications in Statistics—Theory and Methods*, 42,
1176–1192.

1 2 3 4 5 6 | ```
## de Carvalho et al (2013, Fig. 7)
data(beatenberg)
attach(beatenberg)
fit <- angdensity(beatenberg, tau = 0.98, nu = 163, raw = FALSE)
plot(fit)
rug(fit$w)
``` |

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