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Technometrics
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Estimation of the generalized extreme-value distribution by the method of probability-weighted moments

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Abstract

We use the method of probability-weighted moments to derive estimators of the parameters and quantiles of the generalized extreme-value distribution. We investigate the properties of these estimators in large samples, via asymptotic theory, and in small and moderate samples, via computer simulation. Probability-weighted moment estimators have low variance and no severe bias, and they compare favorably with estimators obtained by the methods of maximum likelihood or sextiles. The method of probability-weighted moments also yields a convenient and powerful test of whether an extreme-value distribution is of Fisher-Tippett Type I, II, or III. © 1985 Taylor & Francis Group, LLC.

Date

01 Jan 1985

Publication

Technometrics

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