Development and Applications of the Type II Half-Logistic Inverse Weibull Distribution

Authors

  • Yakubu Isa Federal Polytechnic Kaltungo, Gombe State
  • Radiya Muhammad Said Federal Polytechnic Kaltungo, Gombe State
  • Juliet Wallen Piapna Federal Polytechnic Kaltungo, Gombe State
  • Abdulhaq Bashir Federal Polytechnic Kaltungo, Gombe State

Keywords:

Type II Half-Logistic Exponentiated-G, Inverse Weibull distribution, Hazard function, Reliability function, Maximum likelihood, Order Statistics

Abstract

Communication in Physical Sciences, 2024, 11(4): 721-733

Author: Yakubu Isa*, Radiya Muhammad Said, Juliet Wallen Piapna’an and Abdulhaq Bashir

Received: Received: 24 May 2024/Accepted: 05 August 2024

A variety of distribution classes have emerged by expanding or generalizing well-known continuous distributions to enhance their flexibility and adaptability across various fields. One such distribution is the Inverse Weibull (IW) distribution, introduced by Keller and Kanath in 1982, which has proven effective in modelling failure characteristics. Over the years, several extensions of the IW distribution have been developed, including the Beta Inverse Weibull, Kumaraswamy-Inverse Weibull, and many others. This paper introduces a novel extension called the Type II Half-Logistic Inverse Weibull (TIIHLEtIW) distribution, derived from the Type II Half-Logistic Exponentiated-G (TIIHLEt-G) family proposed by Bello et al. in 2021. The TIIHLEtIW distribution incorporates two additional shape parameters, enhancing its flexibility. We provide the cumulative distribution function (cdf), probability density function (pdf), and key statistical properties, including moments, moment-generating function, reliability function, hazard function, and quantile function. Maximum likelihood estimation (MLE) is employed for parameter estimation, and a simulation study evaluates the performance of the MLEs. Finally, the applicability and superiority of the TIIHLEtIW distribution are demonstrated through a comparative study using two real datasets, showcasing its improved fit over several established distributions.

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Author Biographies

Yakubu Isa, Federal Polytechnic Kaltungo, Gombe State

School of Science and Technology

Radiya Muhammad Said, Federal Polytechnic Kaltungo, Gombe State

School of Science and Technology

Juliet Wallen Piapna, Federal Polytechnic Kaltungo, Gombe State

School of Science and Technology

Abdulhaq Bashir, Federal Polytechnic Kaltungo, Gombe State

School of Science and Technology

References

Abbas, S., Hameed, M., Cakmakyapan, S., & Malik, S. (2010). On gamma inverse Weibull distribution. Journal of the National Science Foundation of Sri Lanka, 47, 4, pp. 445-453, 3, doi: 10.4038/jnsfsr.v47i4.8520

Abbas, S., Taqi, S. A., Mustafa, F., Murtaza, M., & Shahbaz, M. Q. (2017). Topp-Leone inverse Weibull distribution: theory and application. European Journal of Pure and Applied Mathematics, 10, 5, pp. 1005- 1022.

Akanji, B. O., Doguwa, S. I., Abubakar, Y., & Mohammed, J. H. (2023). The properties of Type II Half-Logistic exponentiated Weibull distribution with Applications. UMYU Scientifica, 2, 1, pp. 39-52

Alkarni, S., Afify, A. Z., Elbatal, I., & Elgarhy, M. (2020). The extended inverse Weibull distribution: properties and applications. Complexity, 1, 3297693, https://doi.org/10.1155/2020/3297693

Bello, O. A., Doguwa, S. I., Yahaya, A., & Jibril, H. M. (2021). A Type II Half Logistic Exponentiated-G Family of Distributions with Applications to Survival Analysis. FUDMA Journal of Sciences, 5, 3, pp. 177-190.

Bello, O. A., Doguwa, S. I., Yahaya, A., and Jibril, H. M. (2021). A Type I Half Logistic Exponentiated-G Family of Distributions: Properties and Application. Communication in Physical Sciences, 7, 3, pp. 147-163.

Bhatti, F. A., Hamedani, G. G., Yousof, H. M., Ali, A., & Ahmad, M. (2020). On modified burr xii-inverse weibull distribution: development, properties, characterizations and applications. Pakistan Journal of Statistics and Operation Research, 16, 4, pp. 721-735. https://doi.org/10.18187/ -pjsor.v16i4.2622

David, H. A. (1970). Order statistics, Second edition. Wiley, New York.

De Gusmao, F. R., Ortega, E. M., & Cordeiro, G. M. (2011). The generalized inverse Weibull distribution. Statistical apers, 52, pp. 591-619.

Elbatal, I., Condino, F., & Domma, F. (2016). Reflected generalized beta inverse Weibull distribution: definition and properties. Sankhya B, 78, 2, pp. 316-340.

Fayomi, A. (2019). The odd Frechet inverse Weibull distribution with application. Journal of Nonlinear Sciences and Applications, 12, pp. 165-172.

Greenwood, J.A. Landwehr, J.M., and Matalas, N.C. (1979). Probability weighted moments: Definitions and relations of parameters of several distributions expressible in inverse form. Water Resources Research, 15, pp. 1049-1054.

Keller, A. Z., & ARR, K. (1982). Alternate reliability models for mechanical systems. Proceeding of the 3rd International Conference on Reliability and Maintainability, 411-415.

Khan, M. S. (2010). The beta inverse Weibull distribution. International Transactions in Mathematical Sciences and Computer, 3, 1, pp. 113-119.

Khan, M. S., & King, R. (2016). New generalized inverse Weibull distribution for lifetime modeling. Communications for Statistical Applications and Methods, 23, 2, pp. 147-161.

Pakungwati, R. M., Widyaningsih, Y., & Lestari, D. (2018). Marshall-Olkin extended inverse Weibull distribution and its application. In Journal of physics: conference series, 1108, 1, 012114

Shahbaz, M. Q., Shahbaz, S., & Butt, N. S. (2012). The Kumaraswamy–Inverse Weibull Distribution. Pakistan journal of statistics and operation research, 8, 3, pp. 479-489.

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Published

2024-08-12