半变系数模型的变窗宽和一步局部M-估计

讨论了半变系数模型的变窗宽一步局部M-估计.用一步局部M-估计给出了未知函数的估计,用平均法给出了未知参数的估计,并在其中嵌入一个变窗宽加以提高,得到了未知函数和未知参数的渐近正态性.     

部分线性回归模型变窗宽一步局部M-估计

讨论了部分线性回归模型的变窗宽一步局部M-估计.用一步局部M-估计给出未知函数的估计,用平均方法给出参数估计.进一步通过两个引理证明一步M-估计的渐近正态性.所提出的方法继承了局部多项式的优点并且克服了最小二乘法缺乏稳健性的缺点.     

部分线性模型回归系数估计的渐近分布

考虑部分线性模型Ｙ＝Ｘ‘β＋ｇ（Ｔ）＋ｅ，ｘ∈Ｄ，ｔ∈「０，１」，β为未知的参数向量，ｇ为未知函数，Ｃｈｅｎ给出此模型的一种估计如下，先用分段多项式逼近ｇ，然后用最小二乘法估计β，「１」得到估计量β的渐近正态性。因其渐近分布中含有未知参数，不能直接用于检验问题。     

分块半相依线性回归模型的参数估计

考虑一般的分块半相依线性回归（SUR）模型及其相应的简约模型，给出简约模型下未知回归系数及其可估函数的协方差改进估计仍是分块SUR模型下相应参数的协方差改进估计的一个充要条件．     

部分线性单指标模型的M-估计

单指标模型是一类非常重要的半参数回归模型,不仅可以降低数据维数,克服多元数据中的"维数祸根"问题,而且能抓住高维数据的主要特征.文章研究部分线性单指标模型的M-估计,利用B-样条近似技术逼近非参数函数,提出了获得模型中未知参数M-估计的方法,在一些正则条件下,研究了回归函数以及回归系数的M-估计的渐近性质.随机模拟结果表明了文中M-估计具有稳健性.     

相依数据下一般函数核估计的一致收敛速度

不论数据是独立的还是相依的,在非参数和半参数模型中,都涉及到对未知均值函数或者对某函数的未知条件期望的估计.本文针对这一问题,在比较弱的条件下,给出在数据是α-混合相依时一般函数的条件数学期望的估计,并讨论了它的一致收敛速度.     

具有测量误差的非线性模型的Bayes估计

测量中大量的函数模型都是非线性回归模型．当回归变量含有一定的测量误差时，我们得到非线性测量误差模型．本讨论了这种模型中未知参数具有正态先验分布时的参数Bayes估计方法，并对这种估计进行了影响分析，证明了删除模型与均值漂移模型中参数的Bayes估计相同，利用Cook统计量给出了删除模型下参数的Bayes估计的影响度量．     

次序统计量给出的线性Bayes估计

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是的线性Ｂａｙｅｓ估计，并就特殊分布给出了例子。     

Panel模型中两步估计的优良性

本文研究Panel模型中未知参数的估计问题，给出了两步估计的协方差的准确表达式．用均方误差作为度量估计的优劣标准，我们建立了两步估计优于Within估计和最小二乘估计的充要条件．特别我们获得了两步估计优于Within估计的简单充分条件．一般说来，对于中等数量的样本容量，两步估计就优于Within估计，类似的结论对Between估计或最小二乘估计也成立．     

半参数变量含误差函数关系模型的小波估计

本文研究半参数变量含误差函数关系模型，应用小波估计法和全最小二乘法得出未知参数和未知函数的估计，在一般的条件下，证明了估计的强相合性、一致强相合性，并给出了误差方差估计的强收敛速度。     

纵向数据下部分线性模型的渐近性质

纵向数据是在实际应用中很常见的一种数据类型,在解决实际问题时建立纵向数据模型,进行统计分析很实用。本文研究一类重要的纵向数据下部分线性回归模型,所分析的纵向数据是随机观测而得到的,根据纵向数据的特性构造模型中未知参数分量和未知函数的估计量,进而研究了估计量的渐近性质,通过实例分析,证实了该方法的有效性和可操作性,有很好的使用价值。     

Robust control system design for polytopic stable LPV systems

We investigate robust control system design for polytopic stablelinear parameter-varying (LPV) plants using prior and non-real-timeknowledge of the parameter. A gain-scheduled framework and robustmodel matching (RMM) strategy are combined to develop controllers.First, a self-scheduled H-infinity method is applied to designa nominal controller using a known parameter. Then a robustcompensator is added in order to reduce the influence of parameterperturbation due to the real parameter's deviation from thenominal parameter. Thus, a RMM design method that is a practicalapproach to the design of attachable robust compensators forthe linear time-invariant plant, is extended in applicationto the LPV plant. Finally, robust stability of the overall systemfor possible parameter trajectories is confirmed. A design exampleand simulation results are presented in order to demonstratethe proposed method.     

随机变时滞不确定性系统的鲁棒稳定性

本文讨论了一类随机变时滞不确定性线性微分系统的鲁棒稳定性。参数的不确定性表现为参数是随时间变化的未知函数,但是时范数有界的。利用线性矩阵不等式和Lyapunov函数的方法给出一些相关的稳定性结论。     

矩阵损失函数下回归系数矩阵的非齐次线性估计的可容许性

在二次矩阵损失函数下研究了协方差矩阵未知的多元线性模型中回归系数矩阵的可估线性函数的矩阵非齐次线性估计的可容许性,给出了矩阵非齐次线性估计在线性估计类中可容许的一个充要条件.     

Efficient estimation of a varying-coefficient partially linear binary regression model

This article considers a semiparametric varying-coefficient partially linear binary regression model. The semiparametric varying-coefficient partially linear regression binary model which is a generalization of binary regression model and varying-coefficient regression model that allows one to explore the possibly nonlinear effect of a certain covariate on the response variable. A Sieve maximum likelihood estimation method is proposed and the asymptotic properties of the proposed estimators are discussed. One of our main objects is to estimate nonparametric component and the unknowen parameters simultaneously. It is easier to compute, and the required computation burden is much less than that of the existing two-stage estimation method. Under some mild conditions, the estimators are shown to be strongly consistent. The convergence rate of the estimator for the unknown smooth function is obtained, and the estimator for the unknown parameter is shown to be asymptotically efficient and normally distributed. Simulation studies are carried out to investigate the performance of the proposed method.     

On Newton's method for Huber's robust M-estimation problems in linear regression

The Newton method of Madsen and Nielsen (1990) for computing Huber's robust M-estimate in linear regression is considered. The original method was proved to converge finitely for full rank problems under some additional restrictions on the choice of the search direction and the step length in some degenerate cases. It was later observed that these requirements can be relaxed in a practical implementation while preserving the effectiveness and even improving the efficiency of the method. In the present paper these enhancements to the original algorthm are studied and the finite termination property of the algorithm is proved without any assumptions on the M-estimation problems. Research supported by NATO Collaborative Research Grant CRG-94-0609.     

Robustness of dual divergence estimators for models satisfying linear constraints

We consider new classes of estimators and test statistics for models satisfying linear constraints with unknown parameter. These procedures are based on minimization of divergences through duality techniques. We prove that, for various divergences, the new approach provides robust estimation and test procedures, unlike the empirical likelihood method. We give general results using the influence function approach, which we exemplify in detail in the case of the Cressie–Read divergences. It is found that the Hellinger distance is one of the divergences that leads to robust procedures.     

弱有限元方法在线弹性问题中的应用

本文考虑弱有限元（简称WG）方法在线弹性问题中的应用.WG方法是传统有限元方法的推广,用于偏微分方程的数值求解.和传统有限元一样,它的基本思想源于变分原理.WG方法的特点是使用在剖分单元内部和剖分单元边界上分别有定义的分片多项式函数（即弱函数）作为近似函数来逼近真解,并针对弱函数定义相应的弱微分算子代入数值格式进行计算.除此之外,WG方法允许在数值格式中引进稳定子以实现近似函数的弱连续性.WG方法具有允许使用任意多边形或多面体剖分,数值格式与逼近函数构造简单,易于满足相应的稳定性条件等优点.本文考虑WG方法在求解线弹性问题中的应用.围绕线弹性问题数值求解中常见的三个问题,即：数值格式的强制性,闭锁性,应力张量的对称性介绍WG方法在线弹性问题求解中的应用.     

Optimal guaranteed cost control of uncertain discrete time-delay systems

This paper considers the problem of robust guaranteed cost control of linear discrete time-delay systems with parametric uncertainties. By matrix inequality approach, the robust quadratic stability of the system is studied. A control design method is developed such that the closed-loop system with a cost function has a upper bound irrespective of all admissible parameter uncertainties and unknown time delays. Furthermore, the upper bound (cost) can be optimized by incorporating with a minimization problem. A numerical example is given to show the potential of the proposed techniques.