一类Lindley模型参数的经验Bayes检验收敛速度的改进

Improvement of Convergence Rates of Empirical Bayes Test for Parameters of a Class of Lindley Model

利用递归核估计和单调性,构造了Lindley模型参数的经验Bayes检验函数,并在适当的条件下,证明了收敛速度的阶可任意接近O(n^(-1)).

Through the recursive kernel estimation and the monotone,the empirical Bayes test rules are constructed for parameters of a class of Lindley model.The order of the convergence rates can be arbitrartily close to O(n^(-1))under suitable conditions.