容许估计

词组短语

tolerance estimation

与容许估计相关的网络例句 [注：此内容来源于网络，仅供参考]

In this paper, we study characterizations of admissible in the general linear model Y, Xβ,ε|ε～(0,σ~2∑. We demonstrate that an admissible linear estimator is as the conditional generalized ridge-type estimation in the no constraint, equality constraint, inequality constraint general linear model. We study the superiority of this conditional generalized ridge-type estimation, and prove that it is superior to the restricted best linear unbiased estimator in terms of mean squares. We also give the choice of the matrix K.

本文主要研究了一般线性模型Y，Xβ，ε|ε～(0，σ~2∑中参数估计的可容许性特征，得到了一般线性模型在无约束，有等式约束及有不等式约束下，可容许线性估计均具有条件广义岭估计的形式的结论，并且讨论了这一条件广义岭估计的优良性，证明了其在均方误差和均方误差矩阵意义下都优于约束最小二乘估计，给出了参数矩阵K的选取方法。

We first state general linear model, ridge-type estimator and general ridge-type estimator, and the constraint biased estimator. And then, we introduce some basic theory about matrix and some conclusion about the admissibility of estimator in Gauss-Markov model. In the third chapter, we discussion several equivalent characterization of the best linear unbiased estimation, we proved that admissible characterization of admissible of linear estimation is as conditional general ridge-type estimation in general linear model. A necessary and sufficient condition that homogeneous linear estimator is admissible estimator is obtained.

本文首先概述了一般线性模型，岭估计及约束岭估计的发展历史和研究现状，在第二章介绍了矩阵的一些基本知识和可容许性的一些基本结论，第三章讨论了一般线性模型最佳线性无偏估计的几个等价条件，以及线性估计的可容许性特征，得到了一般线性模型的可容许线性估计均具有条件广义岭估计的形式，给出了一个齐次线性估计为可容许估计的充分必要条件。

And then some ellipses that AUGR estimator is better than the OLS estimator and AUGL estimator is better than the OLS estimator are given, respectively.Second, the definition of the almost unbiased unified biased estimator is proposed. This definition includes the familiar almost unbiased estimators in literatures, and it is the unified expression of the familiar almost unbiased estimators. Followed the biased and variance are compared of AUUB estimator and the unified biased estimator, respectively. AUUB estimator has smaller bias than UB estimator and the variance of AUUB estimator is between the variance of UB estimator and 4 times of the variance of UB estimator. Finally the properties of AUUB estimator are discussed. The conclusion is gained that there are parameters made AUUB estimator is better than OLS estimator in terms of their mean square error. The sufficient and necessary condition that AUUB estimator is admissible is given. The ellipse is given that AUUB estimator is

然后给出了几乎无偏统一有偏估计的定义，该定义包括了文献中常见的几乎无偏估计，实现了常见几乎无偏估计的统一表达式；接下来我们比较了几乎无偏统一有偏估计与统一有偏估计的偏度与方差，得出了几乎无偏统一有偏估计比统一有偏估计有较小的偏度，几乎无偏统一有偏估计的方差介于统一有偏估计的方差与统一有偏估计的方差的四倍之间的结论；最后我们对统一有偏估计的主要性质作了讨论，证明了存在参数K，S使得几乎无偏统一有偏估计在均方误差意义下优于最小二乘估计的结论，给出了几乎无偏统一有偏估计为可容许估计的充要条件，还给出了在均方误差阵意义下几乎无偏统一有偏估计优于最小二乘估计的椭球。

The Minimax admissibility of linear estimates with respect to restricted multivariate regression coefficient under matrix loss function is considered.

在矩阵损失下给出了带约束的多元回归系数线性估计在线性估计类中是 Minimax可容许估计的充要条件。

In the fourth chapter, we discussion the characterization of admissible in the general linear model under equality constraint and inequality constraint, we give the necessary and sufficient condition that homogeneous linear estimator is admissible estimator, and by using the relationship between homogeneous and inhomogeneous linear estimator, we obtain the characterization of admissible inhomogeneous linear estimator.

第四章分别在带等式约束条件以及不等式约束条件下，讨论了一般线性模型线性估计的可容许性特征，给出了在约束条件下齐次线性估计为可容许估计的充分必要条件，同时利用齐次线性估计与非齐次线性估计之间的关系，把齐次线性估计的可容许性特征推广到了非齐次线性估计的可容许性特征。

Combining NA samples the EB estimation with convergence rates is also obtained; Thirdly, for one-parameter exponential distribution family, we give the parameters' EB estimator that is admissible and asymptotically optimal with convergence rates. Finally, Bayesian and hierarchical Bayesian approaches are applied to analyze the reliability performances for series system with cold standby units and the numerical simulation results show that multiple Bayes estimator is superior to Bayes estimator.

其次，针对一类双边截断分布族，在非对称linex损失下构造了经验Bayes决策函数，建立了它的收敛速度，给出了渐近最优的证明；并结合NA样本研究了参数的经验Bayes估计及其收敛速度；接着给出了指数族参数的经验Bayes估计，证明了它是渐近最优的，也是可容许的，同时也获得了该EB估计的收敛速度；最后，运用Bayes与多层Bayes方法研究了具有冷贮备部件串联系统的可靠性指标的估计，并给出了数值模拟结果，结果表明多层Bayes估计优于Bayes估计。

On the base, using the knowledge about matrix operations, we study the admissibility of parameter estimators in multilinear model and growth curve model.

在此基础上，利用矩阵运算的知识，进一步研究了多元线性模型和增长曲线模型中参数估计的可容许性，获得了参数估计在指定的估计类和全体估计类中可容许的充要条件或充分条件。

And the corresponding sufficient condition can be got with respect to classΓ prior distribution in restricted space.

容许估计的充分条件，并将此方法推广到限制空间中该类先验分布族Γ的情形。

Second,a new estimator called generalized rootpower estimator of regression coefficients in growth curve model is obtained.For the newestimator,its superiority over the LS estimator and the root power estimator,and its admissibilityare proved.Two methods,two kinds of arithmetic of choosing the generalized root powerparameters are introduced.A demonstrative practical example is provided.

对增长曲线模型中的回归系数矩阵提出了一种新的估计——广义根方估计，并证明了通过广义根方偏参数的适当选取可使得该估计在均方误差和均方误差矩阵的意义下优于已有的最小二乘估计估计和根方估计；及证明了广义根方估计是可容许估计；还给出了选取广义根方偏参数的两种方法、算法和应用实例。

Using the result for non-restricted model, we transform the restricted model to common model, and multi collectivity model to single collectivity model, thus, the necessary and sufficient conditions that nonhomogeneous linear estimators for Sβ are admissible in the class of nonhomogeneous linear estimators are obtained which filled the blank for admissibility for restricted linear model.

对线性等式约束的共同均值线性模型，利用无约束单总体模型的现有结果，通过适当变换，把等式约束模型向无约束转换，并把多总体转换为单总体，在矩阵损失下找到了均值参数β的条件可估函数Sβ的线性估计∑mAiyi+a在非齐次线性估计类中可容许的充要条件，填补了等式约束的共同均值线性模型可容许性方i=1面的空白。

与容许估计相关的网络解释 [注：此内容来源于网络，仅供参考]

admissible test：容許性測驗

Admissible estimator 可容估计式 | Admissible test 容许性测验 | Admissible transformations 可容转换

allow for：考虑到,估计到;体谅

all too 太 | allow for 考虑到,估计到;体谅 | allow of 容许(有...),容得

allow of：容许(有...),容得

allow for 考虑到,估计到;体谅 | allow of 容许(有...),容得 | along with 同...一道(一起)

estimate：估计值

对截距项系数和各斜率项系数,给出了自由度(DF),估计值(Estimate),估计的标准误差(Std Error),检验系数为零的t统计量,t统计量的p值,检验共线性的容许度(Tolerance)和方差膨胀因子(Var Inflation).

tolerance estimation：容许估计

容许 tolerance | 容许分布 tolerance distribution | 容许估计 tolerance estimation

tolerance factor：容许因子

tolerance estimation 容许估计 | tolerance factor 容许因子 | tolerance level 耐受水平