A Logistic -Moment-Based Analog for the Tukey -, , , and - System of Distributions
Author(s) -
Todd C. Headrick,
Mohan D. Pant
Publication year - 2012
Publication title -
isrn probability and statistics
Language(s) - English
Resource type - Journals
eISSN - 2090-472X
pISSN - 2090-4711
DOI - 10.5402/2012/245986
Subject(s) - kurtosis , moment (physics) , monte carlo method , skew , mathematics , estimator , statistics , second moment of area , statistical physics , physics , geometry , classical mechanics , astronomy
This paper introduces a standard logistic L-moment-based system of distributions. The proposed system is an analog to the standard normal conventional moment-based Tukey g-h, g, h ,a ndh-h system of distributions. The system also consists of four classes of distributions and is referred to as iasymmetric γ-κ, iilog-logistic γ, iiisymmetric κ ,a ndivasymmetric κL-κR. The system can be used in a variety of settings such as simulation or modeling events—most notably when heavy- tailed distributions are of interest. A procedure is also described for simulating γ-κ, γ, κ ,a ndκL-κR distributions with specified L-moments and L-correlations. The Monte Carlo results presented in this study indicate that estimates of L-skew, L-kurtosis, and L-correlation associated with the γ-κ, γ, κ ,a ndκL-κR distributions are substantially superior to their corresponding conventional product- moment estimators in terms of relative bias and relative standard error.
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