The Alpha-Beta Skew Logistic Distribution: Properties and Applications

  • Hamid Esmaeili Department of Statistics, Persian Gulf University, Bushehr, Iran
  • Fazlollah Lak Department of Statistics, Persian Gulf University, Bushehr, Iran
  • Morad Alizadeh Department of Statistics, Persian Gulf University, Bushehr, Iran
  • Mohammad esmail Dehghan monfared Department of Statistics, Persian Gulf University, Bushehr, Iran
DOI: https://doi.org/10.19139/soic-2310-5070-706
Keywords: Logistic distribution, Maximum likelihood, Moments method, Skew distribution.

Abstract

A new family of skew distributions is introduced by extending the alpha skew logistic distribution proposed by Hazarika-Chakraborty [9]. This family of distributions is called the alpha-beta skew logistic (ABSLG) distribution.Density function, moments, skewness and kurtosis coefficients are derived. The parameters of the new family are estimated by maximum likelihood and moments methods. The performance of the obtained estimators examined via a Monte carlo simulation. Flexibility, usefulness and suitability of ABSLG is illustrated by analyzing two real data sets.

Author Biographies

Hamid Esmaeili, Department of Statistics, Persian Gulf University, Bushehr, Iran
Department of Statistics, Persian Gulf University, Bushehr, Iran
Fazlollah Lak, Department of Statistics, Persian Gulf University, Bushehr, Iran
Department of Statistics, Persian Gulf University, Bushehr, Iran
Morad Alizadeh, Department of Statistics, Persian Gulf University, Bushehr, Iran
Department of Statistics, Persian Gulf University, Bushehr, Iran
Mohammad esmail Dehghan monfared, Department of Statistics, Persian Gulf University, Bushehr, Iran
Department of Statistics, Persian Gulf University, Bushehr, Iran

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Published
2020-02-18
How to Cite
Esmaeili, H., Lak, F., Alizadeh, M., & Dehghan monfared, M. esmail. (2020). The Alpha-Beta Skew Logistic Distribution: Properties and Applications. Statistics, Optimization & Information Computing, 8(1), 304-317. https://doi.org/10.19139/soic-2310-5070-706
Issue
Vol 8 No 1 (2020)
Section
Research Articles
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