均值-CVaR模型的稳健构建方法及其比较研究

传统均值-CVaR模型具有不稳健性,当样本数据存在离群值时,传统均值-CVaR模型获得的投资效果可能会偏离实际情况。针对这一现象,文中将稳健统计思想与传统均值-CVaR模型相结合,构建出稳健均值-CVaR模型以削弱或消除离群值的影响,从而获得较为可靠的投资效果。为了说明稳健改进方法的有效性和可行性,文中进行了模拟实验和实证分析,结果均表明:当数据中不存在离群值时,传统和稳健均值-CVaR模型获得的投资效果基本保持一致;但当数据中存在离群值时,传统均值-CVaR模型获得的投资效果与实际不符,而稳健均值-CVaR模型获得的投资效果仍保持着良好的一致性,说明稳健均值-CVaR模型对离群值具有较好的抗差性和抗干扰性。     

稳健统计(Ⅲ)

1.10稳健化和M估计 我们看到正态方法(最小二乘法)不能抵抗(阻尼)离群值的破坏性大影响,它的破坏点为0,影响函数是无界的,总之,它是不稳健的.它可以被改造成稳健方法,这种修正的过程称为稳健化;或者找到另一种代用的稳健方法,称为稳健代用品. 由主观判断识别出离群值;或者用离群值检验诊断的办法,识别出离群值,然后剔除离群值,对于剩余样本用传统的正态方法。这样,实际上已实现了稳健化.L估计中有许多稳健方法,例如,样本中位数、切尾均值都是稳健位置估计.另外,可以从非参数统计中找到稳健代用品。例如R估计就是由(不依赖于总体分布的)秩…     

关于稳健正态序列的讨论

§1 引言稳健性是估计量的优良性质的描述。当原来的估计量具有稳健性时,自然希望对应的Bootstrap估计也保持这一性质。郑忠国[1]提出关于估计序列的稳健性定义,给出了估计序列稳健渐近正态的定义,简称稳健正态序列(RNS)。本文§2依照Hampel的属性稳健性定义,对郑忠国提出的稳健正态性进行了讨论。并且给出了随机加权的稳健条件。指出对一类L—估计,随机加权法具有稳健性。§3讨论了BootstrappingM—估计的稳健性。     

稳健统计(Ⅰ)

稳健统计是60年代兴起、80年代初初步定型的.笔者首次标触它时,很难理解它的统计思想.本讲座介绍稳健统计,不求理论上的系统性,只希望有助于理解稳健统计的基本概念及基本方法的统计思想. 全文分为三个部分:一是讲稳健统计的基本概念,分为第一、第二篇;二是介绍稳健回归;三是介绍多元分析中的稳健方法,主要是位置向量和协方差阵的稳健估计,以及稳健主成分分析.总共四篇.这里不涉及时间序列的稳健性问题 1.1关于基本假定 统计分析是在一定的基本假定下进行的.我们最熟悉的统计方法,诸如,样本均值估计总体均值μ,样本方差S~2=((X_1-X)~2+…+…     

产品失效率的验前分布稳健性分析

研究Bayes统计分析中利用验前信息的稳健性.首先,用一般方法研究了指数寿命型分布中失效率的验前分布的稳健性.然后利用Gamma分布函数的典型性质,并以平方损失下的后验期望损失为判别准则,讨论了失效率的最优Bayes稳健区间.给出了失效率的最优Bayes稳健点估计.     

模糊线性回归的稳健方法

考虑两类模糊回归模型：一类是设计点为实数,参数为模糊数;另一类是观察值为模糊数、参数为实数。就这两类回归模型,从稳健统计的角度提出相应的稳健方法,并通过例子与现有的方法进行比较,说明所提方法的稳健性。     

Meta回归模型的异常值识别及其修正

基于异常值对异质性参数和回归系数估计同时影响的这一新视角下,文章利用方差加权异常值模型(variance-weight outlier model,VWOM)研究了随机效应Meta回归模型的多个异常值识别及其修正问题。首先,推导出Meta回归VWOM分别使用ML和REML估计方法的Score (SC)检验统计量,并考虑Meta回归VWOM的三种扰动方式,包括全局方差扰动,个体方差扰动和随机误差扰动,证明了三种方差扰动的SC检验统计量是等价的。其次,基于异常值对异质性参数和回归系数估计同时影响的考虑,提出了随机效应Meta回归方差加权异常值修正模型(variance-weight outlier modified model,VWOMM),并给出了VWOMM参数的ML和REML估计迭代算法并进行数值求解。此外,通过随机模拟分析验证了SC检验统计量的尺度和功效。最后,利用两个不同类型效应量异常值识别及其处理的实例分析结果,表明了Meta回归VWOM的SC检验统计量识别效果较为显著,VWOMM能有效改善模型拟合程度,为识别和处理复杂数据的异常值提供了一种新的思路和方法。     

稳健性概念浅说

<正> 几乎从高斯提出了正态律和最小二乘法的时候起,就有了“稳健性”的萌芽.但稳健统计得以迅速发展并成为新兴的数理统计分支,还是近十几年的事.七十年代,“稳健”一词成为时髦的字眼,今天它仍然经常出现在各种统计文献中.然而我国数理统计界对它的了解尚不普遍.本文,试图以通俗的语言,对稳健性概念作粗浅的介绍,内容涉及稳健性的含义、重要性、历史背景及其与别的分支的关系等.     

纵向数据均值和协方差矩阵的有效稳健估计（英文）

本文提出一种针对纵向数据回归模型下的均值和协方差矩阵同时进行的有效稳健估计.基于对协方差矩阵的Cholesky分解和对模型的改写,我们提出一个加权最小二乘估计,其中权重是通过广义经验似然方法估计出来的.所提估计的有效性得益于经验似然方法的优势,稳健性则是通过限制残差平方和的上界来达到.模拟研究表明,和已有的针对纵向数据的稳健估计相比,所提估计具有更高的效率和可比的稳健性.最后,我们把所提估计方法用来分析一组实际数据.     

协变量缺失情形下的逆概率加权众数回归估计

数据缺失在实际应用中普遍存在,数据缺失会降低研究效率,导致参数估计有偏.在协变量随机缺失(MAR)的假定下,本文基于众数回归和逆概率加权估计方法对线性模型进行参数估计.该方法结合参数Logistic回归和非参数Nadaraya-Watson估计两种倾向得分估计方法,分别构建IPWM-L估计量和IPWM-NW估计量.模拟研究和实例分析表明,众数回归模型比均值回归模型更具稳健性,逆概率加权众数(IPWM)估计方法在缺失数据下表现出了更好的拟合效果,与IPWM-L估计量相比, IPWM-NW估计量更稳健.     

RECENT PROGRESS ON SPHERICAL HARMONIC APPROXIMATION MADE BY BNU RESEARCH GROUP ——In memory of Professor Sun Yongsheng

As early as in 1990, Professor Sun Yongsheng, suggested his students at Beijing Normal University to consider research problems on the unit sphere. Under his guidance and encouragement his students started the research on spherical harmonic analysis and approximation. In this paper, we incompletely introduce the main achievements in this area obtained by our group and relative researchers during recent 5 years （2001-2005）. The main topics are： convergence of Cesaro summability, a.e. and strong summability of Fourier-Laplace series; smoothness and K-functionals; Kolmogorov and linear widths.     

A unified approach to certain problems of best local approximation

In this paper we study best local quasi-rational approximation and best local approximation from finite dimensional subspaces of vectorial functions of several variables. Our approach extends and unifies several problems concerning best local multi-point approximation in different norms.     

Boundedness for commutators of multipliers on Hardy type spaces

In this paper, we study the commutators generalized by multipliers and a BMO function. Under some assumptions, we establish its boundedness properties from certain atomic Hardy space Hb^p（R^n） into the Lebesgue space L^p with p 〈 1.     

THE 8~(th) INTERNATIONAL CONGRESS ON INDUSTRIAL AND APPLIED MATHEMATICS

<正>August 10-14,2015Beijing,ChinaThe International Congress on Industrial and Applied Mathematics(ICIAM)is the premier international congress in the field of applied mathematics held every four years under the auspices of the International Council for Industrial and Applied Mathematics.From August 10 to 14,2015,mathematicians,scientists     

Towards Excellence in Science Chinese Academy of Sciences

<正>May 26,2014,Beijing Science is a human enterprise in the pursuit of knowledge.The scientific revolution that occurred in the 17th Century initiated the advances of modern science.The scientific knowledge system created by     

Bounds for the zeros of polynomials

Let P(z)=∑↓j=0↑n ajx^j be a polynomial of degree n. In this paper we prove a more general result which interalia improves upon the bounds of a class of polynomials. We also prove a result which includes some extensions and generalizations of Enestrǒm-Kakeya theorem.     

Boundedness of commutators related to Marcinkiewicz integrals on hardy type spaces

In this paper, the authors study the boundedness of the operator [μΩ, b], the commutator generated by a function b ∈ Lipβ(Rn)(0 ＜β≤ 1) and the Marcinkiewicz integrals μΩ, on the classical Hardy spaces and the Herz-type Hardy spaces in the case Ω∈ Lipα(Sn-1)(0 ＜α≤ 1).     

Jacobi polynomials used to invert the laplace transform

Given the Laplace transform F(s) of a function f(t), we develop a new algorithm to find an approximation to f(t) by the use of the classical Jacobi polynomials. The main contribution of our work is the development of a new and very effective method to determine the coefficients in the finite series expansion that approximation f(t) in terms of Jacobi polynomials. Some numerical examples are illustrated.     

Generalization of the interaction between Haar approximation and polynomial operators to higher order methods

In applications it is useful to compute the local average empirical statistics on u. A very simple relation exists when of a function f（u） of an input u from the local averages are given by a Haar approximation. The question is to know if it holds for higher order approximation methods. To do so, it is necessary to use approximate product operators defined over linear approximation spaces. These products are characterized by a Strang and Fix like condition. An explicit construction of these product operators is exhibited for piecewise polynomial functions, using Hermite interpolation. The averaging relation which holds for the Haar approximation is then recovered when the product is defined by a two point Hermite interpolation.