高维线性模型的稀疏半参有效估计

高维线性回归估计是一个被大量学者研究的重要统计学问题.在误差分布未知的情况下,如何将有效性纳入高维估计仍是一个尚未解决且具有挑战性的问题.最小二乘估计在非Gauss误差密度下会损失估计的效率,而极大似然估计由于误差密度未知,无法直接被应用.基于惩罚估计方程,本文提出一种新的稀疏半参有效估计方法应用于高维线性回归的估计.本文证明了在误差密度未知的超高维回归下,新的估计渐近地与具有神谕性的极大似然估计一样有效,因此对于非Gauss误差密度,它比传统的惩罚最小二乘估计更有效.此外,本文证明了几种常用的高维回归估计是本文方法的特例.模拟和实际数据的结果验证了本文所提出方法的有效性.     

Ⅰ型双删失下逆Rayleigh分布的统计分析

在Ⅰ型双删失样本下,用极大似然法得到了逆Rayleigh分布尺度参数估计的迭代公式.根据遗失信息原则计算出了Fisher信息矩阵,由极大似然估计的渐近正态性得到了参数的置信区间.取共轭先验分布,在平方损失函数下,求得了未知参数、可靠度函数的贝叶斯估计和参数的等尾置信区间.根据后验预测密度函数,得到了预测值的估计.通过Monte Carlo随机模拟,得到了多种估计值,并进行了比较,结果表明在小样本场合贝叶斯估计要优于极大似然估计.     

带Gauss型误差的GMANOVA-MANOVA模型中未知参数的精确置信域

对于带Gauss型误差的GMANOVA-MANOVA模型,在均匀协方差结构下,求出了其中未知参数的极大似然估计及其均值和方差,并依据极大似然估计构造了未知参数的精确置信域.     

有限混合Laplace分布回归模型局部估计的EM算法

本文研究了一类有限混合Laplace分布回归模型的局部极大似然估计问题. 利用核回归方法和最大化局部加权似然函数的EM算法, 获得了参数函数的局部极大似然估计量, 并讨论了它们的渐近偏差, 渐近方差和渐近正态性. 推广了有限混合回归模型下局部非参数估计的结果.     

Pareto分布环境因子的估计及其应用

给出了Pareto分布环境因子的定义,讨论了在定数截尾样本下Pareto分布环境因子的极大似然估计和修正极大似然估计,并尝试把环境因子用于可靠性评估中.最后运用Monte Carlo方法对极大似然估计,修正极大似然估计和可靠性指标的均方误差(MSE),进行了模拟比较,结果表明修正极大似然估计优于极大似然估计且考虑环境因子的可靠性评估结果较好.     

上证股指极值模型估计和VaR计算

POT极值模型参数的准确估计是计算金融资产回报厚尾分布市场风险的关键.由n阶概率加权矩得到参数的二项式回归估计,而将参数的零,一阶概率加权矩估计予以推广.极大似然估计中.将极大化似然函转化为二元函数无条件极值问题·其他参数估计方法的结果作为迭代的初始值,通过它们的似然函数值和极大似然函数值的比较以及迭代次数判断方法的优劣.实证研究表明:参数的零、一阶概率加权矩估计较接近于真值,随着阶数的提高,二项式回归参数估计的误差很大.参数的极大似然估计优于非线性回归估计优于零、一阶概率加权矩估计.在此基础上计算上证A股指数vaR值.     

带自回归过程的单指标模型的参数估计及其渐近性质

研究了带有一阶自回归误差结构的单指标模型的参数估计及其渐近性质问题,利用局部多项式回归的方法对未知的联系函数进行估计,基于最大似然方法提出了模型的参数估计方法,同时在一些基本的假设下证明了估计的相合性及其渐近正态性,并给出模拟计算和应用实例以表明所提方法的有效性.     

非正则位置参数模型中的拟极大似然估计

当分布密度的形式未知时，参数的极大似然估计没有明确的解析表达式，也不能通过设计算法由计算机运算得到。本文我们将从该分布中抽取的样本当作是来自另一个形式已知的分布密度的样本，该已知分布密度的选取依赖于未知的分布密度，但是具有与未知分布相似的边界性质。基于这两个分布族，我们提出了拟极大似然估计的概念，同时，对这种拟极大似然估计的渐近性质进行了讨论。结果表明拟极大拟然估计与极大似然估计有关相同的渐近性质，并且由于拟极大似然估计的获得不依赖于未知分布密度的形式，只与一已知的分布密度有关，使得通过计算机可以实现对其的求解。     

带协变量的负二项回归模型中离散参数估计的研究

针对带协变量的负二项回归模型中离散参数估计问题,推广了极大似然估计和Bootstrap极大似然估计方法,并在绝对偏差的意义下,通过模拟研究和实际数据分析研究了估计的优良性.研究结果表明协变量和样本量均对离散参数估计有影响.     

带协变量的负二项回归模型中离散参数估计的研究（英文）

针对带协变量的负二项回归模型中离散参数估计问题,推广了极大似然估计和Bootstrap极大似然估计方法,并在绝对偏差的意义下,通过模拟研究和实际数据分析研究了估计的优良性.研究结果表明协变量和样本量均对离散参数估计有影响.     

A LOCAL MULTILEVEL PRECONDITIONER FOR THE ADAPTIVE MORTAR FINITE ELEMENT METHOD＊

In this paper, we propose a local multilevel preconditioner for the mortar finite element approximations of the elliptic problems. With some mesh assumptions on the interface, we prove that the condition number of the preconditioned systems is independent of the large jump of the coefficients but depends on the mesh levels around the cross points. Some numericM experiments are presented to confirm our theoreticM results.     

MULTISYMPLECTIC FOURIER PSEUDOSPECTRAL METHOD FOR THE NONLINEAR SCHRODINGER EQUATIONS WITH WAVE OPERATOR

In this paper, the multisymplectic Fourier pseudospectral scheme for initial-boundary value problems of nonlinear SchrSdinger equations with wave operator is considered. We investigate the local and global conservation properties of the multisymplectic discretization based on Fourier pseudospectral approximations. The local and global spatial conservation of energy is proved. The error estimates of local energy conservation law are also derived. Numerical experiments are presented to verify the theoretical predications.     

Superlinear and quadratic convergence of some primal-dual interior point methods for constrained optimization

This paper proves local convergence rates of primal-dual interior point methods for general nonlinearly constrained optimization problems. Conditions to be satisfied at a solution are those given by the usual Jacobian uniqueness conditions. Proofs about convergence rates are given for three kinds of step size rules. They are: (i) the step size rule adopted by Zhang et al. in their convergence analysis of a primal-dual interior point method for linear programs, in which they used single step size for primal and dual variables; (ii) the step size rule used in the software package OB1, which uses different step sizes for primal and dual variables; and (iii) the step size rule used by Yamashita for his globally convergent primal-dual interior point method for general constrained optimization problems, which also uses different step sizes for primal and dual variables. Conditions to the barrier parameter and parameters in step size rules are given for each case. For these step size rules, local and quadratic convergence of the Newton method and local and superlinear convergence of the quasi-Newton method are proved. A preliminary version of this paper was presented at the conference “Optimization-Models and Algorithms” held at the Institute of Statistical Mathematics, Tokyo, March 1993.     

差分流线扩散法的局域稳定性分析

本文讨论差分流线扩散法的局部稳定性分析，在理论上证明了该方法依旧保持着流线扩散法扰动局部影响的特性。     

ON NEWTON-HSS METHODS FOR SYSTEMS OF NONLINEAR EQUATIONS WITH POSITIVE-DEFINITE JACOBIAN MATRICES

The Hermitian and skew-Hermitian splitting （HSS） method is an unconditionally convergent iteration method for solving large sparse non-Hermitian positive definite system of linear equations. By making use of the HSS iteration as the inner solver for the Newton method, we establish a class of Newton-HSS methods for solving large sparse systems of nonlinear equations with positive definite Jacobian matrices at the solution points. For this class of inexact Newton methods, two types of local convergence theorems are proved under proper conditions, and numerical results are given to examine their feasibility and effectiveness. In addition, the advantages of the Newton-HSS methods over the Newton-USOR, the Newton-GMRES and the Newton-GCG methods are shown through solving systems of nonlinear equations arising from the finite difference discretization of a two-dimensional convection-diffusion equation perturbed by a nonlinear term. The numerical implemen- tations also show that as preconditioners for the Newton-GMRES and the Newton-GCG methods the HSS iteration outperforms the USOR iteration in both computing time and iteration step.     

Local radial point interpolation method for the fully developed magnetohydrodynamic flow

In this paper, a local radial point interpolation method (LRPIM) is presented to obtain the numerical solutions of the coupled equations in velocity and magnetic field for the fully developed magnetohydrodynamic (MHD) flow through a straight duct of rectangular section with arbitrary wall conductivity and orientation of applied magnetic field. Local weak forms are developed using weighted residual method locally for the governing equations of fully developed MHD flow. The shape functions from LRPIM possess the delta function property. Therefore, essential boundary conditions can be applied as easily as that in the finite-element method. The implementation procedure of LRPIM method is node based, and it doesn’t need any “mesh” or “element”. Computations have been carried out for different Hartmann numbers, wall conductivities and orientations of applied magnetic field.     

A non-interior-point smoothing method for variational inequality problem

In this paper, we focus on the variational inequality problem. Based on the Fischer-Burmeister function with smoothing parameters, the variational inequality problem can be reformulated as a system of parameterized smooth equations, a non-interior-point smoothing method is presented for solving the problem. The proposed algorithm not only has no restriction on the initial point, but also has global convergence and local quadratic convergence, moreover, the local quadratic convergence is established without a strict complementarity condition. Preliminary numerical results show that the algorithm is promising.     

关于总体分布的矩确定

本文引进了局部分布、局部矩、局部矩法估计、样本局部矩和局部分布的矩确定等概念。从而为著名的经典矩量问题提供了新的研究途径与方法并获得了若干新结果。