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L-moments and TL-moments of the generalized lambda distribution by William H. Asquith is a Mathematics article available to read on EtoBox.
What is L-moments and TL-moments of the generalized lambda distribution about?
The 4-parameter generalized lambda distribution (GLD) is a flexible distribution capable of mimicking the shapes of many distributions and data samples including those with heavy tails. The method of L-moments and the recently developed method of trimmed L-moments (TL-moments) are attractive techniques for parameter estimation for heavy-tailed distributions for which the L-and TL-moments have been defined. Analytical solutions for the first five L-and TL-moments in terms of GLD parameters are derived. Unfortunately, numerical methods are needed to compute the parameters from the L-or TL-moments. Algorithms are suggested for parameter estimation. Application of the GLD using both L-and TL-moment parameter estimates from example data is demonstrated, and comparison of the L-moment fit of the 4-parameter kappa distribution is made. A small simulation study of the 98th percentile (far-right tail) is conducted for a heavy-tail GLD with high-outlier contamination. The simulations show, with respect to estimation of the 98th-percent quantile, that TL-moments are less biased (more robost) in the presence of high-outlier contamination. However, the robustness comes at the expense of conside
Who reads L-moments and TL-moments of the generalized lambda distribution?
It is typically read by researchers, students, and practitioners in Mathematics.
- Author
- William H. Asquith
- Publisher
- Elsevier Science; Elsevier ; Elsevier BV (ISSN 0167-9473)
- Published
- 2007
- Language
- EN
- Field
- Mathematics (Physical Sciences)