Log-epsilon-skew normal: A generalization of the log-normal distribution
| Autor: | Terry Mashtare, Govind S. Mudholkar, Alan D. Hutson |
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| Rok vydání: | 2020 |
| Předmět: |
Statistics and Probability
021103 operations research Generalization 0211 other engineering and technologies Skew 02 engineering and technology Function (mathematics) 01 natural sciences Article Normal distribution 010104 statistics & probability Distribution (mathematics) Log-normal distribution Kurtosis Applied mathematics 0101 mathematics Special case Mathematics |
| Zdroj: | Commun Stat Theory Methods |
| ISSN: | 0361-0926 |
| Popis: | The log-normal distribution is widely used to model non-negative data in many areas of applied research. In this paper, we introduce and study a family of distributions with non-negative reals as support and termed the log-epsilon-skew normal (LESN) which includes the log-normal distributions as a special case. It is related to the epsilon-skew normal developed in Mudholkar and Hutson (2000) the way the log-normal is related to the normal distribution. We study its main properties, hazard function, moments, skewness and kurtosis coefficients, and discuss maximum likelihood estimation of model parameters. We summarize the results of a simulation study to examine the behavior of the maximum likelihood estimates, and we illustrate the maximum likelihood estimation of the LESN distribution parameters to two real world data sets. |
| Databáze: | OpenAIRE |
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