Bayesian Estimation of the Exponential Parameter under a Multiply Type-II Censoring Scheme
DOI:
https://doi.org/10.17713/ajs.v36i3.334Abstract
This paper provides the estimation of the scale parameter of the exponential distribution under multiply type-II censoring. Using generalized non-informative prior and natural conjugate prior, Bayes estimator and approximate Bayes estimators of the scale parameter have been obtained under square error loss function. The proposed Bayes estimators and approximate Bayes estimators are compared with the estimators proposed by Singh et al. (2005) and Balasubramanian and Balakrishnan (1992) on the basis of theirsimulated risks under square error loss function of 1000 randomly generated Monte Carlo samples.
References
Balakrishnan, N. (1990). On the maximum likelihood estimation of the parameters of exponential distribution based on multiply-II censored sample. Journal of Applied Statistics, 17, 55-61.
Balasubramanian, K., and Balakrishnan, N. (1992). Estimation for one and two parameter exponential distribution under multiply-II censoring. Statistische Hefte, 33, 203-216.
Lawless, J. F. (1982). Statistical Models & Methods for Lifetime Data. New York: John Wiley and Sons.
Martz, H. F., and Waller, R. A. (1982). Bayesian Reliability Analysis. New York: John Wiley and Sons.
Singh, U., and Kumar, A. (2005a). Shrinkage estimators for exponential scale parameter under multiply type II censoring. Austrian Journal of Statistics, 34, 39-49.
Singh, U., and Kumar, A. (2005b). Bayes estimator for one parameter exponential distribution under multiply-II censoring. Indian Journal of Mathematics amd Mathematical Sciences, 1, 23-33.
Singh, U., Kumar, A., and Upadhyay, S. K. (2005). Maximum likelihood estimators of location and scale parameters of the exponential distribution under multiply-II censoring. Assam Statistical Review, 19, 30-43.
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