Estimation of P(Y < X) in a Four-Parameter Generalized Gamma Distribution

Authors

  • M. Masoom Ali Department of Mathematical Sciences, Ball State University, USA
  • Manisha Pal Department of Statistics, Calcutta University, India
  • Jungsoo Woo Department of Statistics, Yeungnam University, South Korea

DOI:

https://doi.org/10.17713/ajs.v41i3.173

Abstract

In this paper we consider estimation of R = P(Y < X), when X and Y are distributed as two independent four-parameter generalized gamma random variables with same location and scale parameters. A modified maximum likelihood method and a Bayesian technique have been used to estimate R on the basis of independent samples. As the Bayes estimator cannot be obtained in a closed form, it has been implemented using importance sampling procedure. A simulation study has also been carried out to compare the two methods.

References

Ali, M., Pal, M., and Woo, J. (2005). Inference on P(Y < X) in generalized uniform distributions. Calcutta Statistical Association Bulletin, 57, 35-48.

Ali, M., Pal, M., and Woo, J. (2010). Estimation of Pr(Y < X) when X and Y belong to different distribution families. Journal of Probability and Statistical Science, 8, 35-48.

Ali, M., and Woo, J. (2005a). Inference on reliability P(Y < X) in a p-dimensional Raleigh distribution. Mathematical and Computer Modelling, 42, 367-373.

Ali, M., and Woo, J. (2005b). Inference on P(Y < X) in a Pareto distribution. Journal of Modern Applied Statistical Methods, 4, 583-586.

Ali, M.,Woo, J., and Pal, M. (2004). Inference on reliability P(Y < X) in two-parameter exponential distributions. International Journal of Statistical Sciences, 3, 119-125.

Badar, M. G., and Priest, A. M. (1982). Statistical aspects of fiber and bundle strength in hybrid composites. In T. Hayashi, K. Kawata, and S. Umekawa (Eds.), Progress in Science and Engineering Composites, ICCM-IV, Tokyo (1982) (p. 1129-1136).

Basu, A. P. (1964). Estimates of reliability for some distributions useful in reliability. Technometrics, 6, 215-219.

Beg, M. A. (1980). On the estimation of P(Y < X) for two-parameter exponential distribution. Metrika, 27, 29-34.

Chen, M. H., and Shao, Q. M. (1999). Estimation of Bayesian credible intervals and HDP intervals. Journal of Computational and Graphical Statistics, 8, 69-92.

Downtown, F. (1973). The estimation of PrfY < Xg in the normal case. Technometrics, 15, 551-558.

Efron, B. (1982). The Jackknife, the Bootstrap and Other Resampling Plans. Philadelphia, Pennsylvania, USA: Society for Industrial and Applied Mathematics.

Ivshin, V. V. (1996). Unbiased estimators of P(X < Y ) and their variances in the case of uniform and two-parameter exponential distributions. Journal of Mathematical Sciences, 81, 2790-2793.

Iwase, K. (1987). On UMVU estimators of Pr(Y < X) in the 2-parameter exponential case. Memoirs of the Faculty of Engineering, Hiroshima University, 9, 21-24.

Kelley, G. D., Kelley, J. A., and Suchany, W. R. (1976). Efficient estimation of P(Y < X) in the exponential case. Technometrics, 18, 359-360.

McCool, J. I. (1991). Inference on P(X < Y ) in the Weibull case. Communications in Statistcs – Simulation and Computation, 20, 129-148.

Pal, M., Ali, M., and Woo, J. (2005). Estimation and testing of P(Y < X) in twoparameter exponential distributions. Statistics, 39, 415-428.

Raqab, M. Z., and Kundu, D. (2005). Comparison of different estimators of P(Y < X) for a scaled Burr Type X distribution. Communications in Statistcs – Simulation and Computation, 34, 465-483.

Raqab, M. Z., Madi, M. T., and Kundu, D. (2008). Estimation of P(Y < X) for a 3-parameter generalized exponential distribution. Communications in Statistcs – Theory and Methods, 37, 2854-2864.

Tong, H. (1974). A note on the estimation of Pr(Y < X) in the exponential case. Technometrics, 16, 625.

Tong, H. (1977). On the estimation of Pr(Y < X) for exponential families. IEEE Transactions on Reliability, R-26, 54-56.

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Published

2016-02-24

How to Cite

Masoom Ali, M., Pal, M., & Woo, J. (2016). Estimation of P(Y < X) in a Four-Parameter Generalized Gamma Distribution. Austrian Journal of Statistics, 41(3), 197–210. https://doi.org/10.17713/ajs.v41i3.173

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