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Bayesian Estimation of the Reliability Function of the Burr Type XII Model under Asymmetric Loss Function

  • Kim, Chan-Soo (Department of Applied Statistics, Kongju National University)
  • Published : 2007.08.31

Abstract

In this paper, Bayes estimates for the parameters k, c and reliability function of the Burr type XII model based on a type II censored samples under asymmetric loss functions viz., LINEX and SQUAREX loss functions are obtained. An approximation based on the Laplace approximation method (Tierney and Kadane, 1986) is used for obtaining the Bayes estimators of the parameters and reliability function. In order to compare the Bayes estimators under squared error loss, LINEX and SQUAREX loss functions respectively and the maximum likelihood estimator of the parameters and reliability function, Monte Carlo simulations are used.

Keywords

References

  1. AI-Hussaini, E. K. and Jaheen, Z. F. (1992). Bayesian esimation of the parameters, reliability and failure rate functions of the Burr Type XII failure model. Journal of Statistical Computation and Simulation, 41, 31-40 https://doi.org/10.1080/00949659208811389
  2. AI-Hussaini, E. K. and Jaheen, Z. F. (1994). Approximate Bayes estimators applied to the Burr model. Communications in Statistics-Theory and Methods, 23, 99-121 https://doi.org/10.1080/03610929408831242
  3. Ali Mousa, M. A. and Jaheen, Z. F. (2002). Statistical inference for the Burr model based on progressively censored data. Computers & Mathematics with Applications, 43, 1441-1449 https://doi.org/10.1016/S0898-1221(02)00110-4
  4. Burr, I. W. (1942). Cumulative frequency functions. Annals of Mathematical Statistics, 13, 215-222 https://doi.org/10.1214/aoms/1177731607
  5. Chaturvedi, A., Bhatti, M. I. and Kumar, K. (2000). Bayesian analysis of disturbances variance in the linear regression model under asymmetric loss functions. Applied Mathematics and Computation, 114, 149-153 https://doi.org/10.1016/S0096-3003(99)00108-3
  6. Dubey, S. D. (1972). Statistical contributions to reliability engineering. ARL TR 72-0120, AD 774537
  7. Dubey, S. D. (1973). Statistical treatment of certain life testing and reliability problems. ARL TR 73-0155, AD 774537
  8. Moore, D. and Papadopoulos, A. S. (2000). The Burr type XII distribution as a failure model under various loss functions. Microelectronics Reliability, 40, 2117-2122 https://doi.org/10.1016/S0026-2714(00)00031-7
  9. Papadopoulos, A. S. (1978). The Burr distribution as a failure model from a Bayesian approach. IEEE Transactions on Reliability, 27, 369-371 https://doi.org/10.1109/TR.1978.5220427
  10. Lindely, D. V. (1980). Approximate Bayesian methods. Trabajos de Stadistca, 21, 223-237
  11. Thompson, R. D. and Basu, A. P. (1996). Asymmetric Loss Function for Estimating System Reliability. (Berry D. A., Chaloner K. M., Geweke J. K., eds.), Bayesian Analysis in Statistics and Econometrics, John Wiley & Sons, New York
  12. Tierney, L. and Kadane, J. B. (1986). Accurate approximations for posterior moments and marginal densities. Journal of the American Statistical Association, 81, 82-86 https://doi.org/10.2307/2287970
  13. Varian, H. (1975). A Bayesian approach to real estate assessment, (Fienberg S. E. and Zellner A., eds.), Studies in Bayesian Econometrics and Statistics in honour of Leonard J. Savage, North-Holland, Amsterdam, 195-208
  14. Wingo, D. R. (1983). Maximum likelihood methods for fitting the Burr type XII distribution to life test data. Biometrical Journal, 25, 1099-1113
  15. Zellner, A. (1986). Bayesian estimation and prediction using asymmetric loss function. Journal of the American Statistical Association, 81, 446-451 https://doi.org/10.2307/2289234