Comparison of Three-Parameter Weibull Distribution Parameter Estimators with the Maximum Likelihood Method
Year 2022,
Volume: 26 Issue: 6, 1084 - 1092, 31.12.2022
Lazim Kamberi
,
Senad Orhani
,
Mirlinda Shaqiri
,
Sejhan Idrizi
Abstract
Important distributions used to model and analyse data in various real-life sciences such as natural sciences, engineering, and medicine are the Weibull, Weibull exponential, and Weibull Rayleigh distribution. The main objective of this paper is to determine the best evaluators and compare them for the distribution with three-parameters of Weibull, Weibull Rayleigh and Exponential Weibull. The methods under consideration for comparing the parameter estimators for these distributions is that of maximum likelihood using the statistical program R for the application of real data. Based on the results obtained from this study, the maximum likelihood approach used in estimating the parameters is the comparison between these distributions.
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Year 2022,
Volume: 26 Issue: 6, 1084 - 1092, 31.12.2022
Lazim Kamberi
,
Senad Orhani
,
Mirlinda Shaqiri
,
Sejhan Idrizi
References
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- [10] A. L. Morais, W. Barreto-Souza, “A compound class of Weibull and power series distributions”, Computational Statistics and Data Analysis, vol. 55, pp. 1410-1425, 2011.
- [11] A. Choudhury, “A Simple derivation of moments of the exponentiated Weibull distribution”, Metrika, vol. 62, pp. 17-22, 2005.
- [12] A. K. Nanda, H. Singh, N. Misra, P. Paul, “Reliability properties of reversed residual lifetime”, Communications in Statistics-Theory and Methods, vol. 32, pp. 2031-2042, 2003.
- [13] M. M. Nassar, F. H. Eissa, “On the exponentiated Weibull distribution”, Communications in Statistics-Theory and Methods, vol. 32, pp. 1317-1336, 2003.
- [14] R. Tahmasbi, S. Rezaei, “A two-parameter lifetime distribution with decreasing failure rate”, Computational Statistics and Data Analysis, vol. 52, pp. 3889-3901, 2008.
- [15] D. F. Andrews, A. M. Herzberg, “Data: A Collection of Problems from Many Fields for the Student and Research Worker”, Springer Series in Statistics, New York, 1985.
- [16] L. Kamberi, T. Iljazi, S. Orhani, “Statistical Analysis on Information Technology Impact in Quality Learning of Mathematics (for Grades VI-IX)”, Journal of Natural Sciences and Mathematics of UT, vol. 6, no. 11-12, pp. 123-134, 2021.
- [17] F. Merovci, I. Elbatal, “Weibull Rayleigh Distribution: Theory and Applications”, Appl. Math. Inf. Sci. Vol. 9, no. 4, pp. 2127-2137, 2015.