A study of an extension of the exponential distribution using logistic-x family of distributions

  • Authors

    • Pelumi E.Oguntude Covenant University
    • Mundher A.Khaleel Tikrit University
    • Adebowale O.Adejumo University of Ilorin
    • Hilary I.Okagbe Covenant University
    2019-04-03
    https://doi.org/10.14419/ijet.v7i4.26352
  • Exponential Distribution, Generalized Model, Logistic Distribution, Mathematical Statistics, Simulation, Statistical Properties.

  • Abstract

    Compound probability models have played important roles in modeling real life events; their ability to withstand skewed datasets has been attributed to the extra shape parameters they possess. This paper focused on exploring a two-parameter compound distribution; Logistic-X Exponential distribution. The basic mathematical properties of the model were obtained and established. The maximum likelihood method of estimation was adopted in estimating the model parameters. The application and potentials of the Logistic-X Exponential distribution were illustrated with the aid of two real data sets; its performance was also compared with the Logistic distribution and Exponential distribution. A simulation study was performed and the behavior of the model parameters was investigated.

     

     

  • References

    1. [1] M. H. Tahir, G. M. Cordeiro, A. Alzaatreh, M. Mansoor, M. Zubair, The Logistic-X Family of Distributions and Its Applications, Communications in Statistics-Theory and Methods, 45(24), 7326-7349, 2016. https://doi.org/10.1080/03610926.2014.980516.

      [2] N. Eugene, C. Lee, F. Famoye, The beta-normal distribution and its applications, Communication in Statistics-Theory and Methods, 31(4), 497-512, 2002. https://doi.org/10.1081/STA-120003130.

      [3] G. M. Cordeiro, M. de Castro, A new family of generalized distributions, Journal of Statistical Computation and Simulation, 81, 883-898, 2011. https://doi.org/10.1080/00949650903530745.

      [4] P. E. Oguntunde, A. O. Adejumo, H. I. Okagbue, M. K. Rastogi, Statistical Properties and Applications of a New Lindley Exponential Distribution, Gazi University Journal of Science, 29(4), 831-838, 2016.

      [5] G. M. Cordeiro, M. Alizadeh, A. D. C. Nascimento, M. Rasekhi M., the ExponentiatedGompertz Generated Family of Distributions: Properties and Applications, Chilean Journal of Statistics, 7(2), 29-50, 2016.

      [6] P. E. Oguntunde, M. A. Khaleel, M. T. Ahmed, A. O. Adejumo, O. A. Odetunmibi, A New Generalization of the Lomax Distribution with Increasing, Decreasing and Constant Failure Rate, Modelling and Simulation in Engineering, Article ID 6043169, 6 Pages, 2017.

      [7] A. Henningsen, O. Toomet, maxLik: A package for maximum likelihood estimation in R. Computational Statistics, 26(3), 443-458, 2011. https://doi.org/10.1007/s00180-010-0217-1.

      [8] I. B. Abdul-Moniem, M. Seham, Transmuted Gompertz Distribution, Computation and Applied Mathematics, 1(3), 88-96, 2015.

      [9] E. A. Owoloko, P. E. Oguntunde, A. O. Adejumo, Performance Rating of the Transmuted Exponential Distribution: An Analytical Approach, SpringerPlus, 4: 818, 2015. https://doi.org/10.1186/s40064-015-1590-6.

      [10] R. L. Smith, J. C. Naylor, A comparison of maximum likelihood and Bayesian estimators for the three-parameter Weibull distribution, Applied Statistics, 36, 258-369, 1987.

      [11] M. Bourguignon, R. B. Silva, G. M. Cordeiro, The Weibull-G Family of Probability Distributions, Journal of Data Science, 12, 53-68, 2014.

      [12] F. Merovci, M. A. Khaleel, N. A. Ibrahim, M. Shitan M, The Beta Type X Distribution: Properties and Application, SpringerPlus, 5, 697 pages, 2016.

  • Downloads

  • How to Cite

    E.Oguntude, P., A.Khaleel, M., O.Adejumo, A., & I.Okagbe, H. (2019). A study of an extension of the exponential distribution using logistic-x family of distributions. International Journal of Engineering & Technology, 7(4), 5467-5471. https://doi.org/10.14419/ijet.v7i4.26352

    Received date: 2019-01-22

    Accepted date: 2019-01-25

    Published date: 2019-04-03