Minimum sample size determination for generalized extreme value distribution

Cai, Yuzhi; Hames, Dominic

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.

• Journal Article Type: Article
• Acceptance Date: Sep 28, 2010
• Online Publication Date: Jan 20, 2011
• Publication Date: 2010
• Deposit Date: Sep 12, 2023
• Journal: Communications in Statistics: Simulation and Computation
• Print ISSN: 0361-0918
• Electronic ISSN: 1532-4141
• Publisher: Taylor & Francis
• Peer Reviewed: Peer Reviewed
• Volume: 40
• Issue: 1
• Pages: 87-98
• DOI: https://doi.org/10.1080/03610918.2010.530368
• Public URL: https://uwe-repository.worktribe.com/output/11104117
• Publisher URL: https://www.tandfonline.com/toc/lssp20/40/1?nav=tocList