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

Given a dataset with a chosen distribution for the data in the body and another distribution in the tail, the threshold, the parameters of the body and the tail distributions and the weights are estimated.

1 2 3 | ```
fitSpliced(cell, body, tail, method, thresh = NULL)
fitSplicedPar(cell, thresh, body, tail)
``` |

`cell` |
List containing the data in the component cell$Loss |

`body` |
Distribution in the body. Can be chosen between "gamma", "lnorm", "weibull" or "erlang" |

`tail` |
Distribution in the tail. Can be chosen between "gpd", "gamma", "lnorm", "weibull" or "gh" |

`method` |
Method for the threshold estimation. In case of a GPD tail, it can be chosen between "BestFit", "Fixed", "dAMSE", "danielsson", "DK", "hall", "Himp", "HW", "mindist" or "RT" |

`thresh` |
Predetermined threshold quantile (if method="Fixed") |

In the spliced model, the distribution of the data is spliced into two distributions, one in the body and another in the tail.
Given the threshold t, a density function *d1* for the body distribution and a density function *d2* for the tail distribution, the incidental spliced density function
has the formula *d(x)=w*d1(x)* if *x<=t* and *d(x)=(1-w)*d2(x)* of *x>t*.
The weight w is needed to normalize the density function.
The estimation of the spliced distribution consists of three steps.
In the first step, the threshold given chosen body and tail distribution is estimated.
For further details on the methods for the threshold estimation, see fitThreshold.
In the second step, the parameters of the body and the tail distribution are obtained by maximum likelihood estimation.
For spliced distributions, truncated body distributions are fitted to truncated data. For the estimation of the parameters of the tail distribution, only the data points above the threshold are used.
In the last step, the weight w is obtained by maximum likelihood estimation.

Returns a sevdist object of type 'spliced' with the given body and tail distributions fitted to the loss data.

Christina Zou, Leonie Wicht

fitSplicedBestFit, fitThreshold

1 2 | ```
data(lossdat)
fitSpliced(lossdat[[3]],"gamma","gpd",method="Fixed",thresh=2000)
``` |

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.