An Optimal Bayesian Sampling Plan for Two-Parameter Exponential Distribution Under Type-I Hybrid Censoring

Kiran Prajapat, Arnab Koley, Sharmishtha Mitra () and Debasis Kundu
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Kiran Prajapat: Indian Institute of Technology Kanpur
Arnab Koley: Indian Institute of Management Indore
Sharmishtha Mitra: Indian Institute of Technology Kanpur
Debasis Kundu: Indian Institute of Technology Kanpur

Sankhya A: The Indian Journal of Statistics, 2023, vol. 85, issue 1, No 20, 512-539

Abstract: Abstract The Bayesian sampling plan for two-parameter exponential distribution has been considered by Lam (Statistician, 39, 53–66, 1990) under the conventional Type-II censoring. Lin et al. (Commun. Stat.—Simul. Comput., 37, 1101–1116, 2008b) have obtained an exact Bayesian sampling plan for one-parameter exponential distribution under Type-I and Type-II hybrid censoring schemes. In this paper, we obtain an optimal Bayesian sampling plan for the two-parameter exponential distribution under Type-I hybrid censoring scheme based on a four-parameter conjugate prior, introduced by Varde (J. Am. Stat. Assoc., 64, 621–631 1969). Bayes risk expressions of Lam (Statistician, 39, 53–66, 1990) for the conventional Type-II censoring scheme can be obtained as special cases of the Type-I hybrid censoring scheme. The optimal Bayesian sampling plan cannot be obtained analytically, we provide a numerical algorithm to compute the optimal Bayesian sampling plan. Different optimal Bayesian sampling plans have been reported.

Keywords: Exponential distribution; Type-I hybrid censoring; Bayesian sampling plan; Bayes risk; conjugate priors; optimal sampling plan.; Primary 62F10; 62H12; 65D30 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s13171-021-00263-2

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