首页> 外文期刊>Journal of Mathematics and Statistics >Bayesian and Maximum Likelihood Solutions: An Asymptotic Comparison Related to Cost Function | Science Publications
【24h】

Bayesian and Maximum Likelihood Solutions: An Asymptotic Comparison Related to Cost Function | Science Publications

机译:贝叶斯和最大似然解:与成本函数相关的渐近比较科学出版物

获取原文
       

摘要

> Problem statement: Wald showed that the minimax solution is the Bayesian solution with respect to the law a priori the worst. We try to establish a similar result by comparing the Bayesian solution and the solution of maximum likelihood when the parameter space is a compact metrizable group. Approach: we take as a priori law Haar measure because we reduce the problem by invariance. We construct a sequence of cost functions for which we obtain a sequence of solutions Bayesian which converges to the solution of the maximum likelihood. Results: We show that both solutions are asymptotically equal. Conclusion/Recommendation: The generalization when the parameter space is a local compact group.
机译: > 问题陈述: Wald表明,就法律而言,极小极大解是最先验的贝叶斯解。当参数空间是一个紧凑的可度量群时,我们尝试通过比较贝叶斯解和最大似然解来建立相似的结果。方法:我们将其作为先验定律Haar测度,因为我们减少了问题不变。我们构造了成本函数序列,为此我们获得了一系列贝叶斯解,这些贝叶斯解收敛于最大似然解。 结果:我们证明了这两个解在渐近性上是相等的。 结论/建议:参数空间是局部压缩组时的概括。

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