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负相伴样本情形线性指数分布参数的经验Bayes检验问题
Empirical Bayes Test Problem for the Parameter of Linear Exponential Distribution in the Case of Negatively Associated Samples
【摘要】 讨论了负相伴样本情形线性指数分布参数的经验Bayes(EB)单侧检验问题.利用概率密度函数的核估计构造了参数的经验Bayes单侧检验函数,在适当的条件下证明了所提出的经验Bayes检验函数的渐近最优(a.o.)性并获得了其收敛速度.最后给出一个有关主要结果的例子.
【Abstract】 By using the kernel-type density estimation in the case of identically distributed and negatively associated samples,the empirical Bayes one-sided test rules for the parameter of linear exponential distribution are constructed.The asymptotically optimal property and convergence rates for the proposed EB one-sided test rules are obtained under suitable conditions.Finally,an example about the main results of this paper is given.
【关键词】 经验Bayes检验;
渐近最优性;
收敛速度;
负相伴样本;
【Key words】 empirical Bayes test; asymptotic optimality; convergence rates; negatively associated samples;
【Key words】 empirical Bayes test; asymptotic optimality; convergence rates; negatively associated samples;
【基金】 国家自然科学基金(10301011)
- 【文献出处】 数学的实践与认识 ,Mathematics in Practice and Theory , 编辑部邮箱 ,2007年02期
- 【分类号】O212.8
- 【被引频次】8
- 【下载频次】96