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Minimum sample size determination for generalized extreme value distribution. / Yuzhi Cai; Dominic Hames

Communications in Statistics – Simulation and Computation, Volume: 40, Pages: 99 - 110

Swansea University Author: Cai, Yuzhi

Abstract

Sample size determination is an important issue in statistical analysis. Obviously, thelarger the sample size is, the better the statistical results we have. However, in manyareas such as coastal engineering and environmental sciences, it can be veryexpensive or even impossible to collect large samp...

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Published in: Communications in Statistics – Simulation and Computation
Published: 2011
URI: https://cronfa.swan.ac.uk/Record/cronfa11974
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Abstract: Sample size determination is an important issue in statistical analysis. Obviously, thelarger the sample size is, the better the statistical results we have. However, in manyareas such as coastal engineering and environmental sciences, it can be veryexpensive or even impossible to collect large samples. In this paper, we propose ageneral method for determining the minimum sample size required by estimating thereturn levels from a generalized extreme value distribution. Both simulation studiesand the applications to real data sets show that the method is easy to implementand the results obtained are very good.
Keywords: Bootstraping; Generalized extreme value distribution; Return level; Sample size.
College: School of Management
Start Page: 99
End Page: 110