Selection of Parameter-Estimation Method for LP3 Distribution
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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 N ≤ 30, MIX for 30 <N< 100, and any of the four methods for N ≥ 100. When QRI > 1.14, MMO is recommended for N ≤ 30, MIX for 30 <N< 100, and MIX, MMO, or MMI for N ≥ 100. An application procedure was also developed and successfully applied to 10 randomly selected sites in Louisiana.
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Published In
Journal of Irrigation and Drainage Engineering
Volume 122 • Issue 1 • January 1996
Pages: 24 - 30
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Copyright © 1996 American Society of Civil Engineers.
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Published online: Jan 1, 1996
Published in print: Jan 1996
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