Volume 23 , Issue 2 , PP: 186-194, 2024 | Cite this article as | XML | Html | PDF | Full Length Article
Zakariya Yahya Algamal 1 * , Nada Nazar Alobaidi 2 , Abed Ali Hamad 3 , Mazin M. Alanaz 4 , Marwah Yahya Mustafa 5
Doi: https://doi.org/10.54216/IJNS.230215
The beta-Lindley distribution is used in the field of survival analysis to imitate techniques employed with human lifetime data. The neutrosophic beta-Lindley distribution (NBL) is designed to characterize a range of survival statistics with indeterminacies. The established distribution is used, for instance, to describe unknown data that is roughly favorably skewed. The evolved NBL's three main statistical characteristics—the neutrosophic moments, hazard, and survival functions are covered in this article. Additionally, The well-known maximum likelihood estimation method is used to estimate the neutrosophic parameters. To check if the predicted neutrosophic parameters were met, a simulation study was done. Notably, talks of prospective NBL uses in the real world have made use of actual data. Actual data were utilized to show how well the suggested model performed in compared to the current distributions.
Bladder cancer , survival analysis , beta- Lindley distribution , neutrosophic statistics , hazard function.
[1] F. Smarandache, "A unifying field in Logics: Neutrosophic Logic," in Philosophy, ed: American Research Press, 1999, pp. 1-141.
[2] F. Smarandache, Introduction to neutrosophic statistics: Infinite Study, 2014.
[3] F. Smarandache, "Neutrosophic Statistics is an extension of Interval Statistics, while Plithogenic Statistics is the most general form of statistics (second version)," International Journal of Neutrosophic Science, vol. 19, pp. 148-165, 2022.
[4] H. Guan, Z. Dai, S. Guan, and A. Zhao, "A Neutrosophic Forecasting Model for Time Series Based on First-Order State and Information Entropy of High-Order Fluctuation," Entropy (Basel), vol. 21, May 1 2019.
[5] X. Mao, Z. Guoxi, M. Fallah, and S. A. Edalatpanah, "A Neutrosophic-Based Approach in Data Envelopment Analysis with Undesirable Outputs," Mathematical Problems in Engineering, vol. 2020, pp. 1-8, 2020.
[6] M. Aslam, "A New Failure-Censored Reliability Test Using Neutrosophic Statistical Interval Method," International Journal of Fuzzy Systems, vol. 21, pp. 1214-1220, 2019.
[7] F. Taş, S. Topal, and F. Smarandache, "Clustering Neutrosophic Data Sets and Neutrosophic Valued Metric Spaces," Symmetry, vol. 10, 2018.
[8] M. M. Alanaz and Z. Y. Algamal, "Neutrosophic exponentiated inverse Rayleigh distribution: Properties and Applications," International Journal of Neutrosophic Science, vol. 21, pp. 36-42, 2023.
[9] M. M. Alanaz, M. Y. Mustafa, and Z. Y. Algamal, "Neutrosophic Lindley distribution with application for Alloying Metal Melting Point," International Journal of Neutrosophic Science, vol. 21, pp. 65-71, 2023.
[10] A. A. Bibani and Z. Y. Algamal, "Survival Function Estimation for Fuzzy Gompertz Distribution with neutrosophic data," International Journal of Neutrosophic Science, vol. 21, pp. 137-142, 2023.
[11] M. J. N. S. S. Ahsan-ul-Haq, "Neutrosophic Kumaraswamy distribution with engineering application," vol. 49, pp. 269-276, 2022.
[12] M. Albassam, M. Ahsan-ul-Haq, and M. Aslam, "Weibull distribution under indeterminacy with applications," AIMS Mathematics, vol. 8, pp. 10745-10757, 2023.
[13] A. Alsoboh, A. Amourah, M. Darus, and R. I. A. Sharefeen, "Applications of Neutrosophic q-Poisson distribution Series for Subclass of Analytic Functions and Bi-Univalent Functions," Mathematics, vol. 11, 2023.
[14] W.-Q. Duan, Z. Khan, M. Gulistan, A. Khurshid, and Z. Stevic, "Neutrosophic Exponential Distribution: Modeling and Applications for Complex Data Analysis," Complexity, vol. 2021, pp. 1-8, 2021.
[15] C. J. H. J. o. M. Granados and Statistics, "Some discrete neutrosophic distributions with neutrosophic parameters based on neutrosophic random variables," vol. 51, pp. 1442-1457, 2022.
[16] M. K. H. Hassan and M. Aslam, "DUS-neutrosophic multivariate inverse Weibull distribution: properties and applications," Complex & Intelligent Systems, 2023.
[17] Z. Khan, M. M. A. Almazah, O. Hamood Odhah, H. M. Alshanbari, and T. Mehmood, "Generalized Pareto Model: Properties and Applications in Neutrosophic Data Modeling," Mathematical Problems in Engineering, vol. 2022, pp. 1-11, 2022.
[18] Z. Khan, A. Amin, S. A. Khan, M. J. N. S. Gulistan, and Systems, "Statistical development of the neutrosophic Lognormal model with application to environmental data," vol. 47, p. 1, 2021.
[19] G. S. Rao, "Neutrosophic Log-Logistic Distribution Model in Complex Alloy Metal Melting Point Applications," International Journal of Computational Intelligence Systems, vol. 16, 2023.
[20] F. Shah, M. Aslam, Z. Khan, M. M. A. Almazah, F. S. Alduais, and M. Gulzar, "On Neutrosophic Extension of the Maxwell Model: Properties and Applications," Journal of Function Spaces, vol. 2022, pp. 1-9, 2022.
[21] Z. Khan, M. Gulistan, N. Kausar, and C. Park, "Neutrosophic Rayleigh Model With Some Basic Characteristics and Engineering Applications," IEEE Access, vol. 9, pp. 71277-71283, 2021.
[22] M. A. Aslam, "Neutrosophic Rayleigh distribution with some basic properties and application," in Neutrosophic Sets in Decision Analysis and Operations Research, ed: IGI Global, 2020, pp. 119-128.
[23] F. Merovci and V. K. Sharma, "The Beta-Lindley Distribution: Properties and Applications," Journal of Applied Mathematics, vol. 2014, pp. 1-10, 2014.
[24] E. T. Lee and J. Wang, Statistical methods for survival data analysis vol. 476: John Wiley & Sons, 2003.
[25] M. Y. Mustafa and Z. Y. Algamal, "Neutrosophic inverse power Lindley distribution: A modeling and application for bladder cancer patients," International Journal of Neutrosophic Science, vol. 21, pp. 216-223, 2023.
