Document Type
Article
Source Publication Title
ISRN Applied Mathematics
DOI
http://dx.doi.org/10.5402/2012/980827
Abstract
This paper introduces two families of distributions referred to as the symmetric ? and asymmetric ?L-?R distributions. The families are based on transformations of standard logistic pseudo-random deviates. The primary focus of the theoretical development is in the contexts of L-moments and the L-correlation. Also included is the development of a method for specifying distributions with controlled degrees of L-skew, L-kurtosis, and L-correlation. The method can be applied in a variety of settings such as Monte Carlo studies, simulation, or modeling events. It is also demonstrated that estimates of L-skew, L-kurtosis, and L-correlation are superior to conventional productmoment estimates of skew, kurtosis, and Pearson correlation in terms of both relative bias and efficiency when moderate-to-heavy-tailed distributions are of concern.
Disciplines
Curriculum and Instruction | Education
Publication Date
1-1-2012
Language
English
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Headrick, Todd C. and Pant, Mohan, "A method for simulating non-normal distributions with specified L-skew, L-kurtosis, and L-correlation" (2012). Curriculum and Instruction Faculty Publications. 32.
https://mavmatrix.uta.edu/curriculuminstruction_facpubs/32