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A Novel Odd Beta Prime-Logistic Distribution: Desirable Mathematical Properties and Applications to Engineering and Environmental Data

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  • Ahmad Abubakar Suleiman

    (Fundamental and Applied Sciences Department, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia
    Department of Statistics, Aliko Dangote University of Science and Technology, Wudil 713281, Nigeria)

  • Hanita Daud

    (Fundamental and Applied Sciences Department, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia)

  • Narinderjit Singh Sawaran Singh

    (Faculty of Data Science and Information Technology, INTI International University, Persiaran Perdana BBN Putra Nilai, Nilai 71800, Malaysia)

  • Mahmod Othman

    (Department of Information System, Universitas Islam Indragiri, Tembilahan 29212, Indonesia)

  • Aliyu Ismail Ishaq

    (Department of Statistics, Ahmadu Bello University, Zaria 810107, Nigeria)

  • Rajalingam Sokkalingam

    (Fundamental and Applied Sciences Department, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia)

Abstract

In parametric statistical modeling, it is important to construct new extensions of existing probability distributions (PDs) that can make modeling data more flexible and help stakeholders make better decisions. In the present study, a new family of probability distributions (FPDs) called the odd beta prime generalized (OBP-G) FPDs is proposed to improve the traditional PDs. A new PD called the odd beta prime-logistic (OBP-logistic) distribution has been developed based on the developed OBP-G FPDs. Some desirable mathematical properties of the proposed OBP-logistic distribution, including the moments, moment-generating function, information-generating function, quantile function, stress–strength, order statistics, and entropies, are studied and derived. The proposed OBP-logistic distribution’s parameters are determined by adopting the maximum likelihood estimation (MLE) method. The applicability of the new PD was demonstrated by employing three data sets and these were compared by the known extended logistic distributions, such as the gamma generalized logistic distribution, new modified exponential logistic distribution, gamma-logistic distribution, exponential modified Weibull logistic distribution, exponentiated Weibull logistic distribution, and transmuted Weibull logistic distribution. The findings reveal that the studied distribution provides better results than the competing PDs. The empirical results showed that the new OBP-logistic distribution performs better than the other PDs based on several statistical metrics. We hoped that the newly constructed OBP-logistic distribution would be an alternative to other well-known extended logistic distributions for the statistical modeling of symmetric and skewed data sets.

Suggested Citation

  • Ahmad Abubakar Suleiman & Hanita Daud & Narinderjit Singh Sawaran Singh & Mahmod Othman & Aliyu Ismail Ishaq & Rajalingam Sokkalingam, 2023. "A Novel Odd Beta Prime-Logistic Distribution: Desirable Mathematical Properties and Applications to Engineering and Environmental Data," Sustainability, MDPI, vol. 15(13), pages 1-25, June.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10239-:d:1181492
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    References listed on IDEAS

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