Selection of Parameter-Estimation Method for LP3 Distribution

Abstract

The quantile prediction accuracy of the log-Pearson type III (LP3) distribution depends largely on the accuracy of the parameter-estimation method used. The performance of a parameter-estimation method, on the other hand, depends on both the individual population chosen from the LP3 family and the sample size. In this study Monte Carlo experiments were conducted to evaluate four parameter-estimation methods that are frequently used in hydrological analysis. The four methods tested are the method of indirect moments (MMI), the method of mixed moments (MIX), the method of direct moments (MMD), and a modification of MMI using optimization techniques (MMO). A quantile ratio index (QRI) was devised to identify the limits (sample size and LP3 population subset) within which each of these methods will perform best. This study suggests that when QRI ≤ 1.14, MMI or MMO should be used for sample size