Designing Bayesian Sampling Plans with Adaptive Progressive Hybrid Censored Samples | Zendy

TaChen Liang | Zendy

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Designing Bayesian Sampling Plans with Adaptive Progressive Hybrid Censored Samples

Author(s) -

TaChen Liang

Publication year - 2014

Publication title -

advances in statistics

Language(s) - English

Resource type - Journals

eISSN - 2356-6892

pISSN - 2314-8314

DOI - 10.1155/2014/198696

Subject(s) - sampling (signal processing) , computer science , bayesian probability , acceptance sampling , statistics , sampling design , adaptive sampling , importance sampling , mathematics , artificial intelligence , sample size determination , monte carlo method , population , demography , filter (signal processing) , sociology , computer vision

This paper studies the acceptance sampling for exponential distributions with type-I and type-II adaptive progressive hybrid censored samples. Algorithms are proposed for deriving Bayesian sampling plans. We compare the performance of the proposed sampling plans with the sampling plans of Lin and Huang (2012). The numerical results indicate that the proposed sampling plans outperform the sampling plans of Lin and Huang (2012)

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