| Автор | Fong, Duncan K.H. |
| Дата выпуска | 1992 |
| dc.description | A hierarchical Bayesian approach to the problem of estimating the largest normal mean is considered. Calculation of the posterior mean and the posterior variance involves, at worst, 3-dimensional numerical integration, for which an efficient Monte Carlo method of evaluation is given. An example is presented to illustrate the methodology. In the two populations case, computation of the posterior estimates can be substantially simplified and in special cases can actually be performed using closed form solutions. A simulation study has been done to compare mean square errors of some hierarchical Bayesian estimators that are expressed in closed forms and several existing estimators of the larger mean. |
| Формат | application.pdf |
| Издатель | Gordon and Breach Science Publishers |
| Копирайт | Copyright Taylor and Francis Group, LLC |
| Тема | Hierarchical Bayes |
| Тема | largest mean |
| Тема | estimation |
| Тема | exchangeability |
| Тема | Monte Carlo integration with antithetic acceleration |
| Тема | simulation comparison |
| Название | A bayesian approach to the estimation of the largest normal mean |
| Тип | research-article |
| DOI | 10.1080/00949659208811370 |
| Electronic ISSN | 1563-5163 |
| Print ISSN | 0094-9655 |
| Журнал | Journal of Statistical Computation and Simulation |
| Том | 40 |
| Первая страница | 119 |
| Последняя страница | 133 |
| Аффилиация | Fong, Duncan K.H.; The Pennsylvania State University |
| Выпуск | 1-2 |
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