应用极值理论计算VaR的一种方法

在险价值(value at risk，简称VaR)是度量市场风险的一种普遍使用的工具，也是金融风险管理中的基础工具。计算VaR有许多不同的方法，本考虑了数据间的相关性，通过部分重叠数据分组的方法来计算VaR，发现所得到的VaR更符合实际；另外，我们对分组大小作了研究，发现分组数据大小的幂律存在，并对恒生指数作了具体分析。由此得出计算VaR的合理的数据分组大小。     

高等级公路路线方案的多目标量化优选

应用最小二乘法准则,并改进了层次分析法判断矩阵的构成,获得考虑专家评价水平的诸影响因素权向量;基于集值统计法和属性数学原理,建立了对高等级公路路线方案量化综合评价优选模型,并给出了计算实例.     

Edgeworth Expansions for Studentized Versions of Symmetric Finite Population Statistics

We show the validity of the one-term Edgeworth expansion for Studentized asymptotically linear statistics based on samples drawn without replacement from finite populations. Replacing the moments defining the expansion by their estimators, we obtain an empirical Edgeworth expansion. We show the validity of the empirical Edgeworth expansion in probability.     

应用计算机模式识别技术研究微量元素与健康的关系

介绍了微量元素检测数据的一般统计方法，着重推荐应用计算机模式识别技术统计数据．文中介绍计算机模式识别技术的原理和作者应用该技术在微量元素科学的研究中取得的部分成果．     

Asymptotic distribution of rank statistics under dependencies with multivariate application

By modifying the method of projection, the results of Hajek and Huskova are extended to show the asymptotic normality of signed and linear rank statistics under general alternatives for dependent random variables that can be expressed as independent vectors of fixed equal length. The score function is twice differentiable; the regression constants are arbitrary; and the distribution functions are continuous, but arbitrary. As an application, a rank transform statistic is proposed for the one-sample multivariate location model. The ranks of the absolute values of the observations are calculated without regard to component membership, and the scored ranks are substituted in place of the observed values. The limiting distribution of the proposed test statistic is shown to be χ² divided by the degrees of freedom under the null hypothesis, and noncentral χ² divided by the degrees of freedom under the sequence of Pitman alternatives.     

考虑专家水平的土木工程质量综合评估模型

应用加权集值统计、属性数学和最小方差等方法 ,建立了考虑专家水平的量化综合评估模型 ,对土木工程质量进行多目标多人的综合评估 ,并给出计算实例 .     

SEISMIC RANDOM VIBRATION ANALYSIS OF LOCALLY NONLINEAR STRUCTURES

A nonlinear seismic analysis method for complex frame structures subjected to stationary random ground excitations is proposed. The nonlinear elasto-plastic behaviors may take place only on a small part of the structure. The Bouc-Wen differential equation model is used to model the hysteretic characteristics of the nonlinear components. The Pseudo Excitation Method (PEM) is used in solving the linearized random differential equations to replace the solution of the less efficient Lyapunov equation. Numerical results of a real bridge show that .the method proposed is effective for practical engineering analysis.     

三维随机分析的响应曲面法

本文采用“响应曲面法”设计了三维随机分析程序，可对多种材料组成的三维结构进行破坏概率计算，并在Ｗｉｎｄｏｗｓ下实现了计算结果的可视化。     

Profile monitoring of reflow process using approximations of mixture second‐order polynomials

Lately, profile monitoring has received considerable attention in the statistical process control research field. This paper proposes a novel monitoring framework for the reflow process data, which uses two goodness‐of‐fit criteria to select the change points in the mixture polynomial model. Among change points, the mixture second‐order polynomials are utilized to piecewisely approximate the nonlinear profile data of the reflow process. The well‐known Hotelling T² and proposed EWMA₄ control charts are then employed to monitor the parameter estimates. The experimental results demonstrate that the proposed monitoring framework presents better performances in detecting outlying profiles than the conventional methods in phase I. In phase II, the performance of the proposed framework is assessed in terms of the out‐of‐control average run length. Copyright © 2014 John Wiley & Sons, Ltd.     

The beta Laplace distribution

The Laplace distribution is one of the earliest distributions in probability theory. For the first time, based on this distribution, we propose the so-called beta Laplace distribution, which extends the Laplace distribution. Various structural properties of the new distribution are derived, including expansions for its moments, moment generating function, moments of the order statistics, and so forth. We discuss maximum likelihood estimation of the model parameters and derive the observed information matrix. The usefulness of the new model is illustrated by means of a real data set.