估计

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。

SNR maximum likelihood estimator based on data directed decision was evaluated first, and was concluded as a biased estimator. An unbiased estimator can be acquired through high order moments of received data.

摘要通过对基于判决反馈的信噪比最大似然估计推导过程的分析，得出：判决反馈最大似然估计得到的估计值是有偏估计；利用基带数据的高阶矩特性，可以获得渐近无偏估计。

Though the almost unbiased estimator was still a biased estimator, it has smaller bias than corresponding biased estimator.In this paper, we first study the properties of the almost unbiased generalized ridge estimator and the almost unbiased generalized Liu estimator.

但有偏估计毕竟偏离参数的真值，因此学者们又提出了几乎无偏估计的概念，虽然几乎无偏估计仍然是有偏估计，但是它比相应的有偏估计有更小的偏度。

Especially, the combined ratio estimator of domain total is investigated under stratified complemental sampling when auxiliary information can be used.

及该方案在分层抽样下的推广，在有辅助信息可用时构造域总量的分层联合比估计，并给出其方差和方差估计公式，同时我们给出了模拟结果，从模拟结果可以看出，给出的方差估计是估计量方差的近似无偏估计。

Secondly, based on the FO estimate, we formulate the timing error and channel estimation as a problem of composite hypothesis testing according to the first signal model, and then solve the problem by the composite hypothesis testing approaches.

该估计方法包括两步：第一步是根据第二个系统模型，推导了一种有效的最大似然频偏估计器；第二步是根据所获得的频偏估计值，利用第一个系统模型，将定时误差和信道估计表示成一个复合假设检验问题，然后再利用复合假设检验方法进行定时误差和信道估计。

We apply the kernel methods of regression functions and conditional density functions to obtain a series of as the estimators of . Then using Monte Carlo Analysis method , we can get the optimal choice of the unknown parametric that is . Examples illustrate the models and will show this estimation is effective.

应用回归函数核估计和条件密度函数的核估计方法估计未知量，将得到的一组估计值用Monte Carlo Analysis方法处理便得到最优的，并通过算例模拟讨论以上估计方法的优劣。

In the algorithm, the conditional linear state equation is first inserted into the measurement equation, which fuses the linear state process noise and the original measurement noise, whereafter the GHF is used to estimate the nonlinear states. Then the estimated means of the nonlinear states are inserted into the linear state equation and the original measurement equation to estimate the linear states by the KF. Moreover, in order to improve the accuracy of the estimates, the estimated variances of the nonlinear states are fed back to modify the estimations of the linear states using the KF.

算法将模型中的条件线性状态方程代入观测方程，并融合线性状态的过程噪声和观测噪声，由GHF获得非线性状态的估计；再将非线性状态的估计均值代入线性状态方程与观测方程，由KF获得线性状态的估计；获得的非线性状态估计方差还用于修正由KF估计的线性状态，以提高精度。

Based on censored data, a smoothing estimation method is proposed to estimate the parameter functions. Moreover, a consistent estimator for the asymptotic variance matrix of the estimators is provided. The limiting distribution of estimated functions and the estimator of variance matrix enable us to construct approximated regions.

根据截切资料，我们提供平滑估计法以便估计参数函数，接著，我们也对估计函数的变异矩阵提出一个估计式，利用估计式的常态分配逼近，其相对应的信赖区间建构法也被提出。

A knowledge-based correction term in the objective function is proposed. The relationship between state estimatin and parameter estimation is analyzed. A strategy of projecting the objective function from the augmented solution space to the parameter space is proposed and proved.

该文提出基于经验知识的参数估计目标函数修正项，导出状态估计与参数估计目标函数极值的关系，由此提出将目标函数从增广解空间垂直投影到参数空间的估计策略，并指出参数估计偏差的成因。

A method of time delay estimation by two times spectral analysis, where the time delay is the time interval between peaks of spectrum of the cross power spectral density, is proposed in the paper. It can be used to estimate time delay of not only single target but also multi-target without unwrap.

本文提出了两次谱分析时延估计方法，即将互功率谱函数再次进行谱估计，二次谱峰值位置间距即为时延估计，这种方法既能够估计单目标时延，又能够估计多目标时延，并且不用相位解绕。

Methods: Five patients with parkinsonism or dystonia were assigned to general anesthesia using an modified endotracheal tube.

本实验依照人体实验之相关规定进行，五位患有帕金森氏症或肌张力异常的病人接受神经立体定位手术。

If you can benefit from this book, it is our honour.

如果您能从本书获益，这将是我们的荣幸。