A Note on the Estimation of Semiparametric Two-Sample Density Ratio Models

In this paper,a semiparametric two-sample density ratio model is considered and the empirical likelihood method is applied to obtain the parameters estimation.A commonly occurring problem in computing is that the empirical likelihood function may be a concaveconvex function.Here a simple Lagrange saddle point algorithm is presented for computing the saddle point of the empirical likelihood function when the Lagrange multiplier has no explicit solution.So we can obtain the maximum empirical likelihood estimation (MELE) of parameters.Monte Carlo simulations are presented to illustrate the Lagrange saddle point algorithm.     

逐步增加Ⅱ型截尾下指数分布恒加试验的统计分析

本文对逐步增加Ⅱ型截尾下指数分布场合恒定应力加速寿命试验进行了统计分析,得到参数的最大似然估计存在唯一的充要条件。最后通过模拟例子表明最大似然估计是有效的。     

城镇居民非参数消费敏感度模型及应用——基于局部线性工具变量估计方法

建立了城镇居民非参数消费敏感度模型,该模型不需做任何形式假设,避免了线性及非线性模型的误设.采用局部线性工具变量方法对其进行估计,结果表明城镇居民消费敏感度是时变的,和居民收入变动保持同步,支持流动性约束假说.另外高通货膨胀时的负实际利率变动比低利率、温和通胀时造成的负实际利率变动对消费支出的冲击要大得多.因此在增加城镇居民收入,突破流动性约束瓶颈的同时,高度关注通货膨胀,使得其消费水平得到真实提高.     

HR分解的精化扰动界（英文）

给出了HR分解的分量型和范数型的一阶扰动界.对于范数型,新的精化扰动界至少优于已有结果,特别的,新的关于R因子的扰动界远远优于已有的扰动界.     

Combination of structural reliability and interval analysis

In engineering applications, probabilistic reliability theory appears to be presently the most important method, however, in many cases precise probabilistic reliability theory cannot be considered as adequate and credible model of the real state of actual affairs. In this paper, we developed a hybrid of probabilistic and non-probabilistic reliability theory, which describes the structural uncertain parameters as interval variables when statistical data are found insufficient. By using the interval analysis, a new method for calculating the interval of the structural reliability as well as the reliability index is introduced in this paper, and the traditional probabilistic theory is incorporated with the interval analysis. Moreover, the new method preserves the useful part of the traditional probabilistic reliability theory, but removes the restriction of its strict requirement on data acquisition. Example is presented to demonstrate the feasibility and validity of the proposed theory.     

Design of state estimator for uncertain neural networks via the integral-inequality method

The issue of state estimation is studied for a class of neural networks with norm-bounded parameter uncertainties and time-varying delay. Some new linear matrix inequality (LMI) representations of delay-dependent stability criteria are presented for the existence of the desired estimator for all admissible parametric uncertainties. The proposed method is based on the S-procedure and an extended integral inequality which can be deduced from the well-known Leibniz–Newton formula and Moon’s inequality. The results extend some models reported in the literature and improve conservativeness of those in the case that the derivative of the time-varying delay is assumed to be less than one. Two numerical examples are given to show the effectiveness and superiority of the results.     

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在对室内液化石油气泄漏流动过程进行量级估算分析的基础上,提出了一种预测室 内泄漏液化石油气浓度分布的简化方法. 并结合一次居民室内液 化气爆炸事故,讨论了此方法在实际应用中的简易可行性.     

Conditional Source-Term Estimation as a Method for Chemical Closure in Premixed Turbulent Reacting Flow

A Conditional Source-term Estimation (CSE) model is used to close the mean reaction rates for a turbulent premixed flame. A product-based reaction progress variable is introduced as the conditioning variable for the CSE method. Different presumed probability density function (PDF) models are studied and a modified version of a laminar flame-based PDF model is proposed. Improved predictions of the variable distribution are obtained. The conditional means of reactive scalars are evaluated with CSE and compared to the direct numerical simulation (DNS). The mean reaction rates in a turbulent premixed flame are evaluated with the CSE model and the presumed PDFs. Comparison of the CSE closure method to DNS shows promising results. This paper was presented at the 2nd ECCOMAS Thematic Conference on Computational Combustion.     

荧光关联谱的数据处理改进方法

荧光关联谱方法凭借其独特的对溶质浓度及扩散系数的测量能力,在对复杂系统的分子物理化学性质测量方面,不断扩大和深化其应用领域。但是从经典上,传统的荧光关联谱数据处理方法容易在拟合自相关曲线的参数时引入一定的误差,而且图表上的直观信息不多。针对以上问题,在文章中作者尝试用带有微分的数据处理办法,来更直观地估测参数并判断荧光多组分问题。经典自相关曲线处理后的微分曲线,有特异的波谷位置、深度和半深宽度,由此可判断特征扩散时间和多荧光成分的组分数目。此改进方法为利用荧光涨落谱方法测量生物组织体内的复杂环境提供帮助。