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Bayes Estimators of Exponential Parameters from a Censored Sample Using a Guessed Estimate

Authors:

G P Singh ,

Department of Community Medicine, I.M.S., B. H.U., Varanasi, India, IN
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S K Singh,

Department of Community Medicine, I.M.S., B. H.U., Varanasi, India, IN
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Umesh Singh,

Department of Community Medicine, I.M.S., B. H.U., Varanasi, India, IN
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S K Upadhyay

Department of Statistics, C.I.M.S., B. H.U., Varanasi, India, IN
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Abstract

This paper provides the Bayes estimators of the failure rate and reliability function for a one-parameter, exponential distribution by utilizing a point guess estimate of the parameter. For deriving the Bayes estimators, the prior distributions are chosen such that they are centered at the known prior values of parameters. The validity of proposed estimators is examined with respect to their maximum likelihood estimators (MLE) and Thompson's Shrinkage estimator on the basis of Monte Carlo simulations of 1000 samples.
DOI: http://doi.org/10.2481/dsj.7.106
How to Cite: Singh, G.P. et al., (2008). Bayes Estimators of Exponential Parameters from a Censored Sample Using a Guessed Estimate. Data Science Journal. 7, pp.106–114. DOI: http://doi.org/10.2481/dsj.7.106
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Published on 07 Nov 2008.
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