Non-Bayesian estimation of Weibull Lindley burr XII distribution

Document Type : Research Paper

Authors

1 Department of Mathematics, College of Education for Pure Sciences, University of Thi-Qar, Thi-Qar, Iraq

2 Department of Mathematics, University of Thi-Qar, Nasiriyah, Iraq

Abstract

In this paper, we estimate the four parameters of Weibull Lindley burr distribution by using ordinary least square method and multiple regression least square method. The survival estimate made by using ordinary least square estimator (OLSE) and multiple regression estimator (MRE).
 

Keywords

[1] M. A. Al-Fawzan, Methods for estimating the parameters of the Weibull distribution. King Abdulaziz City for Science and Technology, Saudi Arabia (2000).
[2] H. ALkanani and M. A. Abbas , the non Bayesian estimation s method for parameters of exponentiated weibull (Ew) distribution InternationalJournal of Mathematics and statistic, 2(5)(2014)81-94.
[3] H. Al - Nachawati and S. E. Abu  Youssef , A Bayesian Analysis of Order Statistics from the Generalized Rayleigh Distribution, Applied Mathematics Sciences, 3(27)(2009):1315-1325.
[4] A. A. Al- Naqeeb , Suggested Method of Location & Scale Parameters Estimates for Rayleigh distribution According to the Expected Value of the Standardized Order Statistics by Simulation, Al-Tiqani Journal, 23(6)(2010):1-14.
[5] S. F. Ateya, Estimation under modified Weibull distribution based on right censored generalized order statistics. Journal of Applied Statistics, 40(12),(2013) 2720-2734.
[6] S. H. Dhwyia , F. A. Faten , A. I. Nathier and A. A. Hani ,Proposed Methods for Estimating Parameters of the Generalized Rayleigh Distribution in the Presence of One Outlier, American Journal of Mathematics and Statistics, 2(6)(2012):178-183.
[7] N.L. Johnson , S. Kotz, & N. Balakrishnan, Continuous Univariate Distributions, 2nd ed, John Wiley and Sons, Inc., NewYork,USA, Volume 1, (1994), 1-77, .
[8] D. Kundu and M. Z. Raqab , Generalized Rayleigh Distribution: Different Methods of Estimation,Int. J. Modern Math. Sci. 2014, 10(2):103-115
[9] J. Ling, J. Pan, . A new method for selection of population distribu- tion and parameter estimation. Reliability Engineering System Safety, 60(3),(1998) 247-255.
[10] D. C. Montgomery, G. C. Runger, Applied statistics and probability for engineers. John Wiley Sons (2010).
[11] E. Parzen, Nonparametric statistical data modeling. Journal of the American statistical association, 74(365),(1979) 105-121.
[12] F. Parvin , A. Ali and J. K. Hossein , Estimating R = P(Y < X) in the Generalized Rayleigh Distribution with Different Scale Parameters, Applied Mathematics Sciences, 7(2)(2013):87-92.
[13] J. G. Surles, and W. J. Padgett, Inference for Reliability and Stress - Strength for a Scaled Burr Type X Distribution, Lifetime Data Analysis, 7(2001):187-200.
Volume 12, Issue 2
November 2021
Pages 977-989
  • Receive Date: 15 February 2021
  • Revise Date: 24 March 2021
  • Accept Date: 09 April 2021