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http://dx.doi.org/10.29220/CSAM.2021.28.5.563

A class of accelerated sequential procedures with applications to estimation problems for some distributions useful in reliability theory  

Joshi, Neeraj (Department of Statistics, University of Delhi)
Bapat, Sudeep R. (Department of Operations Management and Quantitative Techniques)
Shukla, Ashish Kumar (Department of Statistics, Ramanujan College (University of Delhi))
Publication Information
Communications for Statistical Applications and Methods / v.28, no.5, 2021 , pp. 563-582 More about this Journal
Abstract
This paper deals with developing a general class of accelerated sequential procedures and obtaining the associated second-order approximations for the expected sample size and 'regret' (difference between the risks of the proposed accelerated sequential procedure and the optimum fixed sample size procedure) function. We establish that the estimation problems based on various lifetime distributions can be tackled with the help of the proposed class of accelerated sequential procedures. Extensive simulation analysis is presented in support of the accuracy of our proposed methodology using the Pareto distribution and a real data set on carbon fibers is also analyzed to demonstrate the practical utility. We also provide the brief details of some other inferential problems which can be seen as the applications of the proposed class of accelerated sequential procedures.
Keywords
accelerated sequential; carbon fibers; inverse Gaussian; minimum risk; multivariate normal; negative exponential; normal; Pareto; regret; second-order approximations;
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