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Confidence Intervals and Joint Confidence Regions for the Two-Parameter Exponential Distribution based on Records

  • Asgharzadeh, A. (Department of Statistics, University of Mazandaran) ;
  • Abdi, M. (Department of Statistics, University of Mazandaran)
  • Received : 20100800
  • Accepted : 20101200
  • Published : 2011.01.30

Abstract

Exponential distribution is widely adopted as a lifetime model. Many authors have considered the interval estimation of the parameters of two-parameter exponential distribution based on complete and censored samples. In this paper, we consider the interval estimation of the location and scale parameters and the joint confidence region of the parameters of two-parameter exponential distribution based on upper records. A simulation study is done for the performance of all proposed confidence intervals and regions. We also propose the predictive intervals of the future records. Finally, a numerical example is given to illustrate the proposed methods.

Keywords

References

  1. Arnold, B. C., Balakrishnan, N. and Nagaraja, H. N. (1998). Records, John Wiley and Sons, New York.
  2. Johnson, N. L., Kotz, S. and Balakrishnan, N. (1994). Continuous Univariate Distribution, 1, John Wiley and Sons, New York.
  3. Sun, X., Zhou, X. and Wang, J. (2008). Confidence intervals for the scale parameter of exponential distribution based on Type II doubly censored samples, Journal of Statistical Planning and Inference, 138, 2045-2058. https://doi.org/10.1016/j.jspi.2007.08.006
  4. Wu, S. F. (2007). Interval estimation for the two-parameter exponential distribution based on the doubly type II censored sample, Quality & Quantity, 41, 489-496. https://doi.org/10.1007/s11135-006-9008-8
  5. Wu, S. F. (2010). Interval estimation for the two-parameter exponential distribution under progressive censoring, Quality & Quantity, 44, 181-189. https://doi.org/10.1007/s11135-008-9187-6

Cited by

  1. Multivariate confidence region using quantile vectors vol.24, pp.6, 2017, https://doi.org/10.29220/CSAM.2017.24.6.641