Minimum sample size determination for generalized extreme value distribution

Yuzhi Cai (1) , Dominic Hames (2)

1 School of Computing and Mathematics
2 HR Wallingford Limited

Sample size determination is an important issue in statistical analysis. Obviously, the larger the sample size is, the better the statistical results we have. However, in many areas such as coastal engineering and environmental sciences, it can be very expensive or even impossible to collect large samples. In this paper, we propose a general method for determining the minimum sample size required by estimating the return levels from a generalized extreme value distribution. Both simulation studies and the applications to real data sets show that the method is easy to implement and the results obtained are very good.

Mots clés: Physical Sciences

Yuzhi Cai, Dominic Hames. Minimum sample size determination for generalized extreme value distribution. Communications in Statistics - Simulation and Computation, 2010, 40 (01), pp.87-98. ⟨10.1080/03610918.2010.530368⟩. ⟨hal-00651154⟩