2014
DOI: 10.1016/j.spl.2014.02.022
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On the method of pivoting the CDF for exact confidence intervals with illustration for exponential mean under life-test with time constraints

Abstract: Two requirements for pivoting a cumulative distribution function (CDF) in order to construct exact confidence intervals or bounds for a real-valued parameter θ are the monotonicity of this CDF with respect to θ and the existence of solutions of some pertinent equations for θ. The second requirement is not fulfilled by the CDF of the maximum likelihood estimator of the exponential scale parameter when the data come from some life-testing scenarios such as type-I censoring, hybrid type-I censoring, and progressi… Show more

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Cited by 34 publications
(14 citation statements)
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“…It should be mentioned that the exact confidence intervals of θ 1 and θ 2 may not always exist, see for example Balakrishnan et al [4] for all 0 < α < 1. In fact it is clear that if P θ 1 ( θ 1 ≤ θ 1,obs ) varies from 1 to 0, as θ 1 varies from 0 to infinity, for all values of θ 1,obs , then the exact confidence interval of θ 1 exists for all values of 0 < α < 1.…”
Section: Main Result: Exact Conditional Distributions Of the Mlesmentioning
confidence: 99%
“…It should be mentioned that the exact confidence intervals of θ 1 and θ 2 may not always exist, see for example Balakrishnan et al [4] for all 0 < α < 1. In fact it is clear that if P θ 1 ( θ 1 ≤ θ 1,obs ) varies from 1 to 0, as θ 1 varies from 0 to infinity, for all values of θ 1,obs , then the exact confidence interval of θ 1 exists for all values of 0 < α < 1.…”
Section: Main Result: Exact Conditional Distributions Of the Mlesmentioning
confidence: 99%
“…. , s) and no intermediate inspection points, (6.3) coincides with the system of equations (5) in Xiong and Ji [42]. Further on, for the simple SSALT model, the system (6.3) leads tô…”
Section: Interval Monitored Tfr Step-stress Model Under the Log-linkmentioning
confidence: 72%
“…Note that, in case of time constrained censoring schemes there is a positive (though usually small) probability at least one of the endpoints of the above exact CIs to be infinite, due to solution nonexistence of the respective equations (see Balakrishnan et al [5]). Hence, their expected lengths are infinite.…”
Section: Exact Confidence Intervalsmentioning
confidence: 99%
“…Casella & Berger, , pp. 430–435, Balakrishnan, Cramer, & Iliopoulos, , Hahn, Meeker, & Escobar, ), we need the survival functions of trueϑ^0 and trueϑ^1, respectively. These survival functions are given in Corollary for both options Type‐P and Type‐M.…”
Section: Mle In Sltmentioning
confidence: 99%