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Minimax estimator;Bayes solution;Poisson mean;Restricted space;K-normalized squared error loss;Linear minimax estimator;Weighted squared error loss

中文关键字大中取小估计式;贝氏解;卜阿松分布平均数;限制参数空间;K-正规化平方误差损失;线性大中取小估计式;加权平方误差损失

And others discussed the best linear unbiased estimator for the logistic population.

等又先后讨论了Logistlic分布参数的最佳线性无偏估计及估计的相对效率等问题。

In the fifth chapter, we propose the conditional generalized ridge-type estimator of regression coefficient in restricted linear regression model, and prove that it is superior to the restricted best linear unbiased estimator in terms of mean squares error and mean squares error matrix, we also give the choice of parameters matrix K.

第五章给出了约束线性回归模型中回归系数的条件广义岭估计,讨论了它的优良性,证明了它在均方误差及均方误差矩阵下都优于约束最小二乘估计,并给出了参数矩阵K的选择。

In order to improve the creditableness and robustness of the motion and structure parameters of brachium and leg which are estimated based on dynamic monocular image sequence of human motion, this paper proposes an approach to estimate the human motion using a relative deformation model and the technique of regularization.

为了使根据人体行走的单目动态图象序列,对人体手臂及腿部的运动及结构参数进行估计的结果更为可信、更具鲁棒性,提出了一种基于相对形变模型及正则化技术的人体运动估计方法。

To overcome these disadvantages, the Strong Track Filter is introduced to estimate the motor states, which can improve the estimation performance of abrupt change states and the robustness of variable parameters.

本文利用强跟踪滤波,提出了基于STF的感应电机状态估计算法,有效提高了对于突变状态的估计性能和参数变化的鲁棒性。

Aiming at the problems of over-fitting and generalization for neural networks, the locally most entropic colored Gaussian joint input-output probability density function estimate is studied, and a new method by means of Chebyshev inequality is proposed to self-revise respectively according to every cluster.

针对神经网络的过拟合和泛化能力差的问题,研究了样本数据的输入输出混合概率密度函数的局部最大熵密度估计,提出了运用Chebyshev不等式的样本参数按类分批自校正方法,以此估计拉伸样本集,得到新的随机扩充训练集。

Weibull distribution is widely used as a life distribution, and estimating lower confidence limit of reliability is important. But so far this problem has not been well solved if when the sample size is small.

威布尔分布是使用非常广泛的寿命分布,关于威布尔分布的可靠度的下限估计是一个有重要意义的问题,文献中有很多讨论,但当样本量较小时,关于二参数威布尔分布的可靠度的下限估计至今没有非常有效的方法。

The linear structural EV model studied in the paper can be written aswhere are the observations and measurement error of Xi and yi respectively ,and ij, Xi, ij are p-vectors .The paper presents the estimators of ,.Under some suitable conditions ,strong consistency is obtained .

对于一般线性结构型EV模型,即ξ_=X_i+δ_,η_=y_i+ε_=α+X_i′β+ε_,j=1,…n_i;i=1,…,k,…(0.2)其中ξ_(ij,η_,δ_,ε_分别是自变量X_i和因变量y_i的观测值和观测误差,ξ_,X_i,δ_是p维向量本文给出了参数β,α的估计,并在适当条件下,得到了估计的强相合性。

To solve the problem that the-spectrum estimation performance based on covariation under the-stable noise environmentbecomes obviously worse when the distribution parameter is small,a method of fractional low-order covariance spectrum estimation was proposed.

针对在分布参数值较小时稳定分布噪声下基于共变的谱估计性能较差这一问题,提出了一种分数低阶协方差谱估计方法。

Secondly, by the P-L estimation of survivor function, this paper proposed the regression models of polynomial cumulative hazard function distribution models, respectively in the case of complete date and random right censoring date; meanwhile generalized least squares estimations of unknown parameters were proposed respectively using two steps algorithm and principal component analysis algorithm.

与已有的关于多项式危险函数模型的研究成果相比,首先本文在统计模型的构造上充分考虑了累积危险函数乘积限估计量的非独立性,给出了协方差矩阵的估计;其次在模型检验方面,本文利用非参数回归分析方法,充分利用了数据本身的信息,减少了对回归关系假定的主观因素,因而分析结果更为可靠。

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