Keywords and phrases: weighted Weibull generated family, harmonic mean, inverse exponential distribution, inverse moments, maximum likelihood.
Received: July 2, 2023; Accepted: August 8, 2023; Published: August 23, 2023
How to cite this article: Mohammed Nasser Alshahrani, Weighted Weibull inverse exponential model with application, Advances and Applications in Statistics 89(1) (2023), 55-72. http://dx.doi.org/10.17654/0972361723051
This Open Access Article is Licensed under Creative Commons Attribution 4.0 International License
References: [1] A. Z. Keller and A. R. Kamath, Reliability analysis of CNC machine tools, Reliability Engineering 3 (1982), 449-473. [2] B. Singh and R. Goel, The beta inverted exponential distribution: properties and applications, International Journal of Applied Sciences and Mathematics 2(5) (2015), 132-141. [3] P. E. Oguntunde, A. O. Adejumo and E. A. Owoloko, On the flexibility of the transmuted inverse exponential distribution, Lecture Notes on Engineering and Computer Science: Proceeding of the World Congress on Engineering, London, UK, 2017b, pp. 123-126. [4] P. E. Oguntunde, A. O. Adejumo and E. A. Owoloko, Application of Kumaraswamy inverse exponential distribution to real lifetime data, International Journal of Applied Mathematics and Statistics 56(5) (2017a), 34-47. [5] P. E. Oguntunde, A. O. Adejumo and E. A. Owoloko, On the exponentiated generalized inverse exponential distribution, Lecture Notes on Engineering and Computer Science: Proceeding of the World Congress on Engineering, London, UK, 2017c, pp. 80-83. [6] P. E. Oguntunde, A. O. Adejumo and E. A. Owoloko, The Weibull-inverted exponential distribution: a generalization of the inverse exponential distribution, Lecture Notes on Engineering and Computer Science: Proceeding of the World Congress on Engineering, London, UK, 2017d, pp. 16-19. [7] S. Alrajhi, The odd Fréchet inverse exponential distribution with application, J. Nonlinear Sci. Appl. 12(8) (2019), 535-542. [8] S. Al-Marzouki, Statistical properties of type II Topp Leone inverse exponential distribution, J. Nonlinear Sci. Appl. 14(1) (2021), 1-7. [9] M. Shrahili, I. Elbatal, W. Almutiry and M. Elgarhy, Estimation of sine inverse exponential model under censored schemes, Journal of Mathematics 2021 (2021), Article ID 7330385, 9 pages. [10] Z. Ahmad, G. Hamedani and M. Elgarhy, The weighted exponentiated family of distributions: properties, applications and characterizations, Journal of the Iranian Statistical Society 19(1) (2020), 209-228. [11] A. R. ZeinEldin, Ch. Chesneau, F. Jamal, M. Elgarhy, A. M. Almarashi and S. Al-Marzouki, Generalized truncated Frechet generated family distributions and their applications, Computer Modeling in Engineering and Sciences 126(1) (2021), 1-29. [12] N. H. Al-Noor and L. K. Hussein, Weighted exponential-G family of probability distributions, Saudi Journal of Engineering and Technology 3(2) (2018), 51-59. [13] M. Muhammad, R. A. R. Bantan, L. Liu, C. Chesneau, M. H. Tahir, F. Jamal and M. Elgarhy, A new extended cosine-G distributions for lifetime studies, Mathematics 9 (2021), 2758. [14] H. Bakouch, C. Chesneau and M. Enany, A weighted general family of distributions: theory and practice, Computational and Mathematical Methods 3(6) (2020). https://doi.org/10.1002/cmm4.1135. [15] I. Elbatal, N. Alotaibi, E. M. Almetwally, S. A. Alyami and M. Elgarhy, On odd Perks-G class of distributions: properties, regression model, discretization, Bayesian and non-Bayesian estimation, and applications, Symmetry 14 (2022), 883. [16] M. Hashempour, Weighted Topp-Leone G family of distributions: properties, applications for modelling reliability data and different method of estimation, Hacet. J. Math. Stat. 51(5) (2022), 1420-1441. [17] M. Haq, M. Elgarhy and S. Hashmi, The generalized odd Burr III family of distributions: properties, and applications, Journal of Taibah University for Science 13(1) (2019), 961-971. [18] H. Al-Mofleh, M. Elgarhy, A. Z. Afify and M. S. Zannon, Type II exponentiated half logistic generated family of distributions with applications, Electronic Journal of Applied Statistical Analysis 13(2) (2020), 536-561. [19] R. A. Bantan, F. Jamal, C. Chesneau and M. Elgarhy, Truncated inverted Kumaraswamy generated family of distributions with applications, Entropy 21 (2019), 1089. [20] R. A. Bantan, C. Chesneau, F. Jamal and M. Elgarhy, On the analysis of new COVID-19 cases in Pakistan using an exponentiated version of the M family of distributions, Mathematics 8 (2020), 953. [21] A. Algarni, A. M. Almarashi, I. Elbatal, A. S. Hassan, E. M. Almetwally, A. M. Daghistani and M. Elgarhy, Type I half logistic Burr XG family: properties, Bayesian, and non-Bayesian estimation under censored samples and applications to COVID-19 data, Math. Probl. Eng. 2021 (2021), Article ID 5461130. [22] N. Alotaibi, I. Elbatal, E. M. Almetwally, S. A. Alyami, A. S. Al-Moisheer and M. Elgarhy, Truncated Cauchy power Weibull-G class of distributions: Bayesian and non-Bayesian inference modelling for COVID-19 and carbon fiber data, Mathematics 10 (2022), 1565. [23] M. M. Badr, I. Elbatal, F. Jamal, C. Chesneau and M. Elgarhy, The transmuted odd Fréchet-G family of distributions: theory and applications, Mathematics 8 (2020), 958. [24] A. S. Hassan, A. W. Shawki and H. Z. Muhammed, Weighted Weibull-G family of distributions: theory and application in the analysis of renewable energy sources, Journal of Positive School Psychology 6(3) (2022), 9201-9216. [25] A. Rényi, On measures of entropy and information, Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, Contributions to the Theory of Statistics, Statistical Laboratory of the University of California, Berkeley, CA, USA, Volume 1, 1960, p. 767. [26] C. Tsallis, Possible generalization of Boltzmann-Gibbs statistics, J. Statist. Phys. 52 (1988), 479-487. [27] J. Havrda and F. Charvat, Quantification method of classification processes, concept of structural a-entropy, Kybernetika 3 (1967), 30-35. [28] S. Arimoto, Information-theoretical considerations on estimation problems, Inf. Cont. 19 (1971), 181-194. [29] A. J. Gross and V. A. Clark, Survival Distributions: Reliability Applications in the Biometrical, John Wiley, New York, 1975. [30] A. Abdullah Alahmadi, M. Alqawba, W. Almutiry, A. W. Shawki, S. Alrajhi, S. Al-Marzouki and M. Elgarhy, A new version of weighted Weibull distribution: modelling to COVID-19 data, Discrete Dynamics in Nature and Society Vol. 2022, Article ID 3994361. https://doi.org/10.1155/2022/3994361. [31] M. A. Mobarak, Z. Nofal and M. Mahdy, On size-biased weighted transmuted Weibull distribution, International Journal of Advanced Research in Computer Science and Software Engineering 7(3) (2017), 317-325. [32] S. Dey, T. Dey and M. Z. Anis, Weighted Weibull distribution: properties and estimation, Journal of Statistical Theory and Practice 9 (2015), 250-265. [33] A. Saghir, M. Saleem, A. Khadim and S. Tazeem, The modified double weighted exponential distribution with properties, Mathematical Theory and Modeling 5(8) (2015), 78-91.
|