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bayesian testing
相关语句
  bayes试验
     Representation of Prior Distribution in Bayesian Testing Analysis
     Bayes试验分析中验前分布的表示
短句来源
     Optimal design for bayesian testing assessment of the impact point dispersion of missile
     导弹落点散布的Bayes试验鉴定优化设计
短句来源
  “bayesian testing”译为未确定词的双语例句
     Bayesian testing for fuzzy hypothesis of life characteristics
     寿命特征模糊假设的贝叶斯检验
短句来源
     A fuzzy multiple hypotheses is introduced and the Bayesian testing method is discussed with some examples, for both crisp sample data and fuzzy sample information.
     本文将模糊性引入到多重假设中,从贝叶斯决策的角度,分样本为清晰数据和模糊信息两种情形,研究了多重模糊假设的贝叶斯方法,并给出了数值例。
短句来源
  相似匹配句对
     The Bayesian Sequential Testing Analysis
     关于序贯检验的Bayes分析(英文)
短句来源
     TESTING
     试验
短句来源
     Bayesian Sequential Testing method
     Bayes序贯检验方法
短句来源
     Fitness Testing
     对我院学生身体素质考核情况的调查与分析
短句来源
     ve Bayesian.
     ve Bayesian的贝叶斯网络的模型。
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  bayesian testing
An approach to significance testing by the direct interpretation of likelihood is defined, developed and distinguished from the traditional forms of tail-area testing and Bayesian testing.
      
Bayesian testing of nonparametric hypotheses and its application to global optimization
      
Bayesian testing for trend in a power model for clustered binary data
      
Noninformative Bayesian testing and neutral Bayes factors
      
As a consequence we can give a confidence band for the expected posterior, and we suggest a frequentist refinement for Bayesian testing.
      
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Objective To discuss differences between classical and Bayesian testing thoughts.Methods First these two thoughts are summarized,and then they are compared through an example.Results It is pointed out that these two thoughts are united on Bayes's Theorem,that they are equal on given occasions,and that Bayesian testing approaches have more advantages than classical approaches in using prior information,indicating the hazard of testing,considering the loss,and dealing with the problem of multi...

Objective To discuss differences between classical and Bayesian testing thoughts.Methods First these two thoughts are summarized,and then they are compared through an example.Results It is pointed out that these two thoughts are united on Bayes's Theorem,that they are equal on given occasions,and that Bayesian testing approaches have more advantages than classical approaches in using prior information,indicating the hazard of testing,considering the loss,and dealing with the problem of multi hypotheses.Conclusion Great attention should be paid to Bayesian theory.

目的探讨经典统计学派与贝叶斯学派假设检验思想的异同。方法总结和概括两种思想,并结合一个实例对两种思想进行比较。结果两种思想统一于贝叶斯定理,并在特定场合下相互等价;贝叶斯方法在先验信息的利用、风险的回答、损失的考虑以及多重假设问题的处理等方面较经典方法具有明显的优势。结论贝叶斯学派的理论应用受到重视

In statistical inference and statistical decision, fuzzy concepts are frequently used. An important case is a situation where we are interested in testing the hypotheses that are fuzzy rather than crisp. A fuzzy multiple hypotheses is introduced and the Bayesian testing method is discussed with some examples, for both crisp sample data and fuzzy sample information.

应用统计推断和统计决策问题中,常常需要处理模糊概念,模糊假设检验是其中非常重要的一种情形。本文将模糊性引入到多重假设中,从贝叶斯决策的角度,分样本为清晰数据和模糊信息两种情形,研究了多重模糊假设的贝叶斯方法,并给出了数值例。

The paper studied the traditional tests of an exponential sample and presented a Bayesian test based on the noninformative prior distribution. By using prior distribution of the distributional parameter, test statistics and their post distributional functions were derived from the strict deduction. The example and Monte carlo simulation experiments showed its effectiveness. The test was suitable for the data including upper and lower outliers and could avoid the masking effect of the...

The paper studied the traditional tests of an exponential sample and presented a Bayesian test based on the noninformative prior distribution. By using prior distribution of the distributional parameter, test statistics and their post distributional functions were derived from the strict deduction. The example and Monte carlo simulation experiments showed its effectiveness. The test was suitable for the data including upper and lower outliers and could avoid the masking effect of the data.

研究了指数分布场合异常数据的检验问题 ,提出了无信息先验分布下的Bayes检验方法 .利用分布参数的先验分布严格推导出新的检验统计量及其后验分布函数 .实例和蒙特卡罗模拟表明了方法是可行的 ,适用于同时含有异常大、异常小数据的情形 ,并能够避免遭受屏蔽效应

 
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