• 主题
高级搜索  >
历史搜索 清空历史
首页> 美国政府科技报告 >Selecting the Most Reliable Poisson Population Provided It Is Better Than aControl: A Nonparametric Empirical Hayes Approach
【24h】

Selecting the Most Reliable Poisson Population Provided It Is Better Than aControl: A Nonparametric Empirical Hayes Approach

机译：选择最可靠的泊松群体，只要它比一个控制更好：非参数经验Hayes方法

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

We study the problem of selecting the most reliable Poisson population from amongk competitors provided it is better than a control using the nonparametric empirical Bayes approach. An empirical Bayes selection procedure is constructed based on the isotonic regression estimators of the posterior means of failure rates associated with the k Poisson populations. The asymptotic optimality of the empirical Bayes selection procedure is investigated. Under certain regularity conditions, we have shown that the proposed empirical Bayes selection procedure is asymptotically optimal and the associated Bayes risk converges to the minimum Bayes risk at a rate of order O(exp(-cn)) for some c>0, where n denotes the number of historical data at hand when the present selection problem is considered.

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号