1) asymptotic minimax efficiency
渐近minimax有效
1.
In this paper the MLE of θ,say θ^\-n,from randomly censored data is pr oved to be asymptotic minimax efficiency.
本文证明基于随机删失观察的参数θ的MLEθ^n 是渐近minimax有效的 ,即对某损失函数W (·) ,limδ→ 0 limn→∞ sup|θ′-θ|<δE(n)θ′ {w[- 1(n) (θ^n-θ) ]} =Ew(ξ) ,其中 ,L(ξ) =N(0 ,1) ,p(n) =(nI|θ|) - 12 ,I(θ)是删失观察的信息函数。
3) asymptotic efficiency
渐近有效性
1.
We also discussed some of its asymptotic properties, such as asymptotic consistency, asymptotic efficiency and cost of ignorance, under some certain assumptions.
并讨论了在一定条件下,当d→0,它的渐近相合性、渐近有效性及有界的最优费用差(EN(d)-n(d))等渐近性质。
2.
Some of its asymptotic properties, such as asymptotic consistency, asymptotic efficiency and cost of ignorance under certain conditions, are also discussed.
并讨论了在一定条件下,当d→0时,估计的渐近相合性、渐近有效性及有界的最优费用差(EN(d)?n(d))等渐近性质。
4) effectively asymptotic solutions
有效渐近解
5) asymptotic risk efficient
渐近风险有效
6) Bahadur efficiency
Bahadur渐近有效估计
1.
Based on some smooth conditions, the Bahadur bound for this distribution family is derived, and a definition of Bahadur efficiency is proposed.
基于一定的光滑性假设,得到了这种双边截断分布族的Bahadur界,并因此给出了该分布族中相合估计为Bahadur渐近有效估计的定义。
补充资料:渐近公式
渐近公式
asymptotic formula
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