Estimating extreme value cumulative distribution functions using bias-corrected kernel approaches

Identificador:  PC:2462

Handle: https://hdl.handle.net/20.500.11797/PC2462

Autors:  Alemany Leira, Ramon; Bahraoui, Zuhair; Bolancé Losilla, Catalina

Resum:
We propose a new kernel estimation of the cumulative distribution function based on transformation and on bias reducing techniques. We derive the optimal bandwidth that minimises the asymptotic integrated mean squared error. The simulation results show that our proposed kernel estimation improves alternative approaches when the variable has an extreme value distribution with heavy tail and the sample size is small.