Non-parametric extreme quantile estimation for the common shaped tail model: Forecasting extreme precipitation by post-processing precipitation from a numerical weather prediction model

The estimation of extreme quantile curves of a family of conditional distributions is a non-trivial problem, due to the data-sparseness in the tail of the distribution. This thesis considers the problem of post-processing extreme precipitation forecasts in Friesland from the numerical weather prediction model HARMONIE. Assuming forecasts are...

Estimating the extreme value index for imprecise data

In extreme value theory the focus is on the tails of the distribution. The main focus is to estimate the tail distribution for a rounded data set. To estimate this tail distribution the extreme value index should be estimated, but due to the rounded data this extreme value index oscillates heavily. Therefore a correct estimate can not be...