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Bayesian Estimation of Small Proportions Using Binomial Group Test

Group testing has long been considered as a safe and sensible relative to one-at-a-time testing in applications where the prevalence rate p is small. In this thesis, we applied Bayes approach to estimate p using Beta-type prior distribution. First, we showed two Bayes estimators of p from prior on p derived from two different loss functions. Second, we presented two more Bayes estimators of p from prior on π according to two loss functions. We also displayed credible and HPD interval for p. In addition, we did intensive numerical studies. All results showed that the Bayes estimator was preferred over the usual maximum likelihood estimator (MLE) for small p. We also presented the optimal β for different p, m, and k.

Identiferoai:union.ndltd.org:fiu.edu/oai:digitalcommons.fiu.edu:etd-1854
Date09 November 2012
CreatorsLuo, Shihua
PublisherFIU Digital Commons
Source SetsFlorida International University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceFIU Electronic Theses and Dissertations

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