• Journal of the Korean Data and Information Science Society
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• v.8 no.2
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• pp.261-270
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• 1997

This paper is proposed the parametric empirical Bayes(EB) confidence intervals which corrects the deficiencies in the naive EB confidence intervals of the scale parameter in the Weibull distribution under item-censoring scheme. In this case, the bootstrap EB confidence intervals are obtained by the parametric bootstrap introduced by Laird and Louis(1987). The comparisons among the bootstrap and the naive EB confidence intervals through Monte Carlo study are also presented.

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.155-162
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• 1999

This paper is concerned with the empirical Bayes estimation of one of the two shape parameters(${\theta}$) in the Burr(${\beta},\;{\theta}$) type XII failure model based on type-II censored data. We obtain the bootstrap empirical Bayes confidence intervals of ${\theta}$ by the parametric bootstrap introduced by Laird and Louis(1987). The comparisons among the bootstrap and the naive empirical Bayes confidence intervals through Monte Carlo study are also presented.

• International Journal of Reliability and Applications
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• v.2 no.1
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• pp.49-56
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• 2001

In this paper we consider empirical Bayes estimation of the hazard rate and survival probabilities with right censored data under the assumption that the hazard function is constant over the period of observation and the prior distribution is gamma. We provide an estimator of the first derivative of the prior moment generating function that converges at each point to the true value in $L_2$ and use it to obtain, easy to compute, asymptotically optimal estimators under the squared error loss function.