Parameter estimation for multivariate diffusion processes with the time inhomogeneously positive semidefinite diffusion matrix

Statistical inference for the diffusion coefficients of multivariate diffusion processes has been well established in recent years; however, it is not the case for the drift coefficients. Furthermore, most existing estimation methods for the drift coefficients are proposed under the assumption that the diffusion matrix is positive definite and time homogeneous. In this article, we put forward two estimation approaches for estimating the drift coefficients of the multivariate diffusion models with the time inhomogeneously positive semidefinite diffusion matrix. They are maximum likelihood estimation methods based on both the martingale representation theorem and conditional characteristic functions and the generalized method of moments based on conditional characteristic functions, respectively. Consistency and asymptotic normality of the generalized method of moments estimation are also proved in this article. Simulation results demonstrate that these methods work well.     

A new confidence interval in measurement error model with the reliability ratio known

For the slope parameter of the measurement error model with the reliability ratio known, this article constructs a fiducial generalized confidence interval (FGCI) which is proved to have correct asymptotic coverage. Simulation results demonstrate that the FGCI often outperforms the existing intervals in terms of empirical coverage probability, average interval length, and false parameter coverage rate. Two examples are also provided to illustrate our approach.     

产品广义交互设计的内涵及其价值转向

进入21世纪,产品的交互方式和体验价值成为提升产品竞争力的关键因素,广义的交互性不仅包括传统的人机交互,还涉及到由产品引发的人际交互。传统交互设计主要关注物质维度的实用功能和行为维度的使用方式。当代广义交互设计主要聚焦于自然交互和社会交互,促进技术的人性化和人际和谐,人性价值和社会效应至上,正是广义交互设计的价值取向。     

快速遗传算法研究

提出了一种称为广义自适应遗传算法的快速遗传算法,它首先产生均匀分布的初始种群,其次根据种群模式的状况决定是否引入“高品质”移民,最后自适应地进行交换和变异运算。其搜索性和全局收敛性比现有的许多遣传算法都有明显的改善,并通过仿真说明了该改进遣传算法的有效性。     

极值理论高频VaR区间估计模型的构建

为了对在险值的估计精度进行度量,更为精确和有效地衡量极值VaR（value at risk）的估计风险,基于广义极值理论构建了极值VaR的区间估计模型,并进一步利用高频数据重点考察了不同置信水平和不同样本容量分块下的极值VaR区间估计结果的精度和模型的有效性。结果表明,极值VaR的动态区间估计模型与参数法和非参数法区间估计模型相比,不仅能够更为有效地捕获极端条件下收益率时间序列的动态特征,而且具有很好的估计精度,VaR估计风险的精确度更高。     

自然科学史和大科学史的学科结构

自然科学史经过几百年的演进发展,已经走向初步成熟、能够进行自我认识的阶段.自然科学史已经建立和有待建立的分支学科,可区分为普通科学史、科学综合史、科学学科史、科学社会活动史、专项科学体制史、专项科学成就史七个学科群组.大科学史是指将研究范围延展到包括所有科学部类的科学史.大科学史研究,在分析方向上要特别关注对新兴科学部类的历史审视,在综合方向上要突出对各个科学部类相互关系的历史考察和普通大科学史的相关基础研究.     

特征零域上的广义Cartan型W类李超代数

本文构造了特征零的域F上的广义Cartan型W类李超代数及其子代数Wd,并给出了Wd是单李超代数的充分必要条件。     

论当代知识生产力的新发展

从广义社会生产力的角度,论述了知识生产力的属性,即人们在社会的知识生产中创造和应用知识的能力,它是社会精神生产力的体现,并对社会的物质生产起着日益重要的作用;继而着重探讨了知识生产的基本特点和知识生产力的测度方法,根据当代知识生产的创造性、高投入、高收益与高风险性,提出测度知识生产的投入、产出及知识生产效益的具体方法.     

Asymptotic distribution of regression correlation coefficient for Poisson regression model

This study treats an asymptotic distribution for measures of predictive power for generalized linear models (GLMs). We focus on the regression correlation coefficient (RCC) that is one of the measures of predictive power. The RCC, proposed by Zheng and Agresti is a population value and a generalization of the population value for the coefficient of determination. Therefore, the RCC is easy to interpret and familiar. Recently, Takahashi and Kurosawa provided an explicit form of the RCC and proposed a new RCC estimator for a Poisson regression model. They also showed the validity of the new estimator compared with other estimators. This study discusses the new statistical properties of the RCC for the Poisson regression model. Furthermore, we show an asymptotic normality of the RCC estimator.