Estimation of the Generalized Extreme-Value Distribution by the Method of Probability Weighted Moments.
Abstract
The authors use the method of probability weighted moments to derive estimators of the parameters and quantiles of the generalized extreme-value distribution. They 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 compare favourably 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. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 01, 1984
- Accession Number
- ADA141696
Entities
People
- E. F. Wood
- J. R. M. Hosking
- J. R. Wallis
Organizations
- University of Wisconsin–Madison