Geometric sample size determination in bayesian analysis
Nassar M.; Khamis S.; Radwan S.;
Abstract
The problem of sample size determination in the context of Bayesian analysis is considered. For the familiar and practically important parameter of a geometric distribution with a beta prior, three different Bayesian approaches based on the highest posterior density intervals are discussed. A computer program handles all computational complexities and is available upon request. © 2010 Taylor & Francis.
Other data
| Title | Geometric sample size determination in bayesian analysis | Authors | Nassar M. ; Khamis S. ; Radwan S. | Keywords | Bayesian analysis; average coverage criterion (ACC); average length criterion (ALC); worst-outcome criterion (WOC) | Issue Date | 1-Apr-2010 | Journal | Journal of Applied Statistics | DOI | 4 https://api.elsevier.com/content/abstract/scopus_id/77949523827 567 37 10.1080/02664760902803248 |
Scopus ID | 2-s2.0-77949523827 |
Attached Files
| File | Description | Size | Format | |
|---|---|---|---|---|
| Geometric sample size determination.pdf | 91.49 kB | Adobe PDF | View/Open |
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