Study of the two-parameter Weibull distribution and Estimation of the scale and shape parameter application to the voltage data of the cement material (review)

Section: Review Paper
Published
Jun 25, 2025
Pages
68-77

Abstract

Survival distributions are important and commonly used in different fields and the Weibull Distribution is one of these distributions that has a different formula and the Weibull distribution has been chosen with two parameters, the measurement parameter and the shape parameter, and its properties have been studied and the two distribution parameters have been estimated in two ways, namely the method of greatest possibility and the method of Biz when the information about the parameter is not available (Non-Informative) and when the information about the parameter is available (Informative), What was reached in theory was applied to real data represented by a potentiometer of cement material for seven days.

References

  1. Abbas, K., Abbasi, N. Y., Ali, A., Khan, S. A., Manzoor, S., Khalil, A., & Altaf, M. (2019)," Bayesian analysis of three-parameter Frchet distribution with medical applications"Computational and mathematical methods in medicine.
  2. Ahmad, Kaisar ,(2013), "Bayesian Analysis of Weibull Distribution and Its Application" , A master message that is not published , University of Kashmir , pp . 17_26 .
  3. Bassiouni, K. M. H. (2007). Optimization Neural Network for Blind Signal Separation Using an Adaptive Weibull Distribution. Georgian Electronic Scientific Journal, 11, 68-74.
  4. Bilal, M., Mohsin, M., & Aslam, M. (2021). Weibull-exponential distribution and its application in monitoring industrial process. Mathematical Problems in Engineering, 2021.
  5. Bilici, E. (2021). "Investigation of Feller-Buncher Performance Using Weibull Distribution".Forests,12(3), 284..
  6. Cho, Y., Sun, H., & Lee, K. (2015). Estimating the entropy of a Weibull distribution under generalized progressive hybrid censoring.Entropy,17(1), 102-122.
  7. Kenney, J. F., & Keeping, E. S. (1961)," SkewnessMathematics of Statistics ",Part,1, 100-101.
  8. Murthy, D. P., Xie, M., & Jiang, R. (2004). Weibull models (Vol. 505). John Wiley & Sons.
  9. Nabeshima, T., & Gunji, Y. P. (2004). Zipfs law in phonograms and Weibull distribution in ideograms: comparison of English with Japanese.BioSystems,73(2), 131-139.
  10. Rinne, H. (2008). The Weibull distribution: a handbook. Chapman and Hall/CRC..
  11. Scholz, F. W. (2015). Inference for the Weibull Distribution: A tutorial.The Quantitative Methods for Psychology,11(3), 148-173.
  12. Waheed, m. e. s., and Hashem, k. (2006). Optimization neural Network for Blind Dignal Separation using an Adaptive Weibull Distribution. in georgian electronic scientific journal: computer science and telecommunications.

Identifiers

Download this PDF file

Statistics

How to Cite

Rashed, S., صفوان, Thafer Thafer, F., فاروق, Abdallah Sulayman, A., & علی. (2025). Study of the two-parameter Weibull distribution and Estimation of the scale and shape parameter application to the voltage data of the cement material (review). IRAQI JOURNAL OF STATISTICAL SCIENCES, 19(2), 68–77. Retrieved from https://rjps.uomosul.edu.iq/index.php/stats/article/view/20895