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1)  optimum asymptotic order
最优渐近阶
2)  asymptotically optimal
渐近最优
3)  Convergence and asymptotic order of the regularized solution
渐进最优阶
4)  asymptotic optimality
渐近最优性
1.
Also,a simulation experiment is conducted to demonstrate the asymptotic optimality of the Bayes EB estimator.
我们采用贝叶斯经验贝叶斯方法估计了一个特殊的指数分布族中的刻度参数,证明了刻度参数的贝叶斯经验贝叶斯估计几乎处处收敛到它的贝叶斯估计且获得了它的渐近最优性。
2.
The Bahadur representation of the estimator are given and the asymptotic optimality for L2- cross-validated nearest neighbor median estimator are established under the mild conditions.
在一定的正则性条件下得到了L2-cross-validation最近邻中位数估计的渐近最优性。
3.
There have been a lot of researches about the asymptotic optimality theory,but all of them are based on the Biihlmann-Straub model and quadratic loss function;In this paper, the author will discuss the linear empirical Bayes premiumunder quadratic loss function, balance loss function, entropy~1 loss function and entropy~2 loss function in a general Biihlmann-Straub model.
传统的关于线性经验贝叶斯保费的渐近最优性研究都是在B(u|¨)hlmann-Sraub模型及平方损失函数下讨论的,然而在某些情况下广义B(u|¨)hlmann-Straub模型和非对称损失函数能更好的刻画衡量风险。
5)  asymptotical optimality
渐近最优性
6)  convergence and optimum asymptotic order of the regularized solution
正则解的收敛性与最优渐近阶
补充资料:阶渐
1.循序渐进的途径。
说明:补充资料仅用于学习参考,请勿用于其它任何用途。
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