On statistical intercomparison of EV1 estimators by Monte Carlo simulation
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Extreme value type 1 distribution parameters and quantiles were estimated by methods of moments, maximum likelihood estimation, probability weighted moments, entropy, mixed moments, least squares and incomplete means for Monte Carlo samples generated from two sampling cases: purely random process and serially correlated process. The performance of these estimators was statistically inter-compared. Additionally, a bias correction was made to the method of moments-quantile estimator. The corrected estimator provided nearly unbiased quantile estimates even for small samples and high nonexceedance probabilities. 1987.