Minimum Sample Size Determination for Generalized Extreme Value Distribution

Abstract

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 article, 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.

Keywords:

• Bootstraping
• Generalized extreme value distribution
• Return level
• Sample size

Mathematics Subject Classification:

• 65C60
• 62G32

Acknowledgment

We would like to express our sincere thanks to the referees for their very constructive comments and suggestions which have greatly enhanced the quality and the presentation of the article.