The method of self-determined probability weighted moments revisited

• Published in: Journal of hydrology (Amsterdam) Vol. 268; no. 1; pp. 177 - 191
• Main Authors: Whalen, Timothy M., Savage, Gregory T., Jeong, Garrett D.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.11.2002; Elsevier Science
• Subjects: Earth sciences; Earth, ocean, space; Engineering and environment geology. Geothermics; Exact sciences and technology; Extreme wind speed estimation; Flood peak analysis; Hydrology; Hydrology. Hydrogeology; Natural hazards: prediction, damages, etc; Numerical methods; Parameter estimation; Self-determined probability weighted moments; United States; New Mexico; Self-determined probability weighted moments; Parameter estimation; Flood peak analysis; Numerical methods; Extreme wind speed estimation; algorithms; floods; probability; accuracy; velocity; North America; new methods; winds; methodology; theory
• ISSN: 0022-1694; 1879-2707
• DOI: 10.1016/S0022-1694(02)00174-9

Haktanir originally introduced the method of self-determined probability weighted moments as an extension of the traditional method of probability weighted moments for parameter estimation. While this method possesses many advantages, his algorithms introduced certain mathematical manipulations for numerical convenience or based upon special knowledge of the behavior of a data sample. Also, some of these algorithms relied upon inputs from numerical tables that are not widely accessible. To improve the usefulness of this method, new algorithms have been developed that directly implement the relevant equations and do not rely upon external results. In this paper, we show that these features extend the applicability of self-determined probability weighted moments without loss of accuracy in the parameter estimates. Examples from flood peak analysis and extreme wind speed estimation are presented.