Parameter estimation for the 4-parameter Asymmetric Exponential Power distribution by the method of L-moments using R
Computational Statistics and Data Analysis
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Abstract
The implementation characteristics of two method of L-moments (MLM) algorithms for parameter estimation of the 4-parameter Asymmetric Exponential Power (AEP4) distribution are studied using the R environment for statistical computing. The objective is to validate the algorithms for general application of the AEP4 using R. An algorithm was introduced in the original study of the L-moments for the AEP4. A second or alternative algorithm is shown to have a larger L-moment-parameter domain than the original. The alternative algorithm is shown to provide reliable parameter production and recovery of L-moments from fitted parameters. A proposal is made for AEP4 implementation in conjunction with the 4-parameter Kappa distribution to create a mixed-distribution framework encompassing the joint L-skew and L-kurtosis domains. The example application provides a demonstration of pertinent algorithms with L-moment statistics and two 4-parameter distributions (AEP4 and the Generalized Lambda) for MLM fitting to a modestly asymmetric and heavy-tailed dataset using R.
Suggested Citation
Asquith, W.H., 2014, Parameter estimation for the 4-parameter Asymmetric Exponential Power distribution by the method of L-moments using R: Computational Statistics and Data Analysis, v. 71, p. 955-970, https://doi.org/10.1016/j.csda.2012.12.013.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Parameter estimation for the 4-parameter Asymmetric Exponential Power distribution by the method of L-moments using R |
| Series title | Computational Statistics and Data Analysis |
| DOI | 10.1016/j.csda.2012.12.013 |
| Volume | 71 |
| Year Published | 2014 |
| Language | English |
| Publisher | Elsevier |
| Contributing office(s) | Texas Water Science Center |
| Description | 15 p. |
| Larger Work Type | Article |
| Larger Work Subtype | Journal Article |
| Larger Work Title | Computational Statistics and Data Analysis |
| First page | 955 |
| Last page | 970 |