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线性bayes估计
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  bayes linear estimates
     BAYES LINEAR ESTIMATES OF REGRESSION COEFFICIENT IN A GENERAL GAUSS -MARKOFF MODEL
     Gauss—Markoff模型中回归系数的线性Bayes估计
短句来源
     Bayes Linear Estimates of Regression Coefficients in a Variance Component Model
     方差分量模型中回归系数的线性Bayes估计
短句来源
     In this paper, Bayes linear estimates of regression coefficient in a variance component model are studied both under the quadratic loss function and matrix loss function.
     本文研究了方差分量模型中在平方和损失函数和矩阵损失函数下回归系数的线性Bayes估计
短句来源
  linear bayes estimation
     Linear Bayes Estimation of Location and Scale Parameters Using Order Statistics
     次序统计量给出的线性Bayes估计
短句来源
  empirical bayes estimators
     In this paper , a class of empirical Bayes estimators of parameter 9 is constructed and their asymptotically optimal convergence rates are given.
     本文构造了参数θ的一类线性Bayes估计,并给出了渐近最优的收敛速度。
短句来源
     In this paper,a class of empirical Bayes estimators of parameter θ is constructed and their asymptotically optimal convergence rates are given.
     构造参数θ的一类线性 Bayes估计 ,并给出渐近最优的收敛速度
短句来源
  “线性bayes估计”译为未确定词的双语例句
     In this paper we discussed some properties of linear Bayes ot and linear empirical Bayes estimation.
     本文讨论了线性Bayes估计和线性经验Bayes估计的若干性质。
短句来源
     By means of examples we investigated linear and general Bayes estimation, repectively.
     最后,通过实例研究了线性Bayes估计和一般Bayes估计。
短句来源
     In the class of distributions depending on scale & location parameters only , linear Bayes estimates of the linear functions of these parameters are discusse. An example of rectangular ditributed calculated here.
     本文讨论了位置尺度参数族的参数线性函数的线性Bayes估计问题,给出了基于次序统计量的线性Bayes估计,并就特殊分布给出了例子。
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  empirical bayes estimators
The convergent rate of empirical bayes estimators for parameters of normal distribution family
      
The best uniform convergence rate of linear empirical bayes estimators
      
Estimation of multiple poisson means: A compromise between maximum likelihood and empirical bayes estimators
      
For estimatingp(? 2) independent Poisson means, the paper considers a compromise between maximum likelihood and empirical Bayes estimators.
      
Following the Bayesian paradigm, the Bayes and empirical Bayes estimators relative to various loss functions are obtained.
      
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In consideration of the generalized Gauss-Markoff Model Y = xβ+ε, E(ε) = 0> COV(ε) = σ2V, where X and V≥0 are the known matrices, βεRP and σ2>0 are parameters. Let Sβ be linearly estimable. With respect to the priors of βπ1, Eπ1(β) = 0, Covπ1(β) = σ2W and π2, Eπ2(β) = 0, Covπ2(β) = σ-W under the quadratic loss function and matrix loss function, all Bayes linear estimators are obtained. Some of them are admissible among linear estimators. If Y is a normal vector, a class of admissible estimators of mean β among...

In consideration of the generalized Gauss-Markoff Model Y = xβ+ε, E(ε) = 0> COV(ε) = σ2V, where X and V≥0 are the known matrices, βεRP and σ2>0 are parameters. Let Sβ be linearly estimable. With respect to the priors of βπ1, Eπ1(β) = 0, Covπ1(β) = σ2W and π2, Eπ2(β) = 0, Covπ2(β) = σ-W under the quadratic loss function and matrix loss function, all Bayes linear estimators are obtained. Some of them are admissible among linear estimators. If Y is a normal vector, a class of admissible estimators of mean β among all the estimators under quadratic loss function is obtained.

考虑一般的Gauss-Markoff模型Y=Xβ+ε,E(ε)=0,cov(ε)=σ~2V,其中X,V≥0分别是n×p,n×n已知矩阵,β∈R~P,σ~2>0是未知参数,设Sβ是线性可估的,则在平方损失和矩阵损失下,分别给出了所有线性Bayes估计,并指出一些线性Bayes估计是线性可容许估计,对Y是正态情形给出了一类在整个估计类中是β的可容许的线性Bayes估计

In this paper we discussed some properties of linear Bayes ot and linear empirical Bayes estimation. Under suitable conditions we obtained precise asymptotic behavior of linear empirical Bayes estimator and its conditional Bayes risk. By means of examples we investigated linear and general Bayes estimation, repectively.

本文讨论了线性Bayes估计和线性经验Bayes估计的若干性质。在适当条件下,证得了线性经验Bayes估计和它的条件Bayes风险的精确渐近结构。最后,通过实例研究了线性Bayes估计和一般Bayes估计。

In this paper , a class of empirical Bayes estimators of parameter 9 is constructed and their asymptotically optimal convergence rates are given.

本文构造了参数θ的一类线性Bayes估计,并给出了渐近最优的收敛速度。

 
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