Accurate Calculation of Confidence Intervals on Predicted Extreme Met-Ocean Conditions When Using Small Datasets

Estimation of high return period values of wind and wave conditions is usually done using a limited sample of data from measurement or hindcast studies. Because a finite sample size is used, the reliability of estimates is usually evaluated by constructing confidence intervals around design values such as the 100 year return value. In this paper, a numerical simulation study is used to compare the accuracy of calculated confidence intervals using several different calculation methods: the asymptotic normal, parametric bootstrap and profile likelihood methods. The accuracy of each method for different sample sizes is assessed for the truncated Weibull distribution. Based on these results, a profile likelihood method for estimation of confidence intervals is suggested for use when dealing with small datasets.