在线性损失函数下,对NA样本下一类指数分布族参数咿的经验Bayes单侧检验问题进行了研究.通过构造参数的经验Bayes单侧检验函数,获得了它的渐近最优(a.o)性,在适当条件下得出了所提出的经验Bayes检验函数的收敛速度可以任意接近O(n-1/2).
Based on negatively associated samples, the Empirical Bayes one-sided test rules for the parameter of a class of special exponential distributions are studied under linear loss function. Then the Empirical Bayes one-sided test rules are constructed and the asymptotically optimal property is obtained. It is shown that the convergence rates of the proposed EB test rules can arbitrarily close to O(n-1/2) under suitable conditions.