A semiparametric maximum likelihood ratio test for the change point in copula models

In the present paper, a semiparametric maximum-likelihood-type test statistic is proposed and proved to have the same limit null distribution as the classical parametric likelihood one. Under some mild conditions, the limiting law of the proposed test statistic, suitably normalized and centralized, is shown to be double exponential, under the null hypothesis of no change in the parameter of copula models. We also discuss the Gaussian-type approximations for the semiparametric likelihood ratio. The asymptotic distribution of the proposed statistic under specified alternatives is shown to be normal, and an approximation to the power function is given. Simulation results are provided to illustrate the finite sample performance of the proposed statistical tests based on the double exponential and Gaussian-type approximations.     

线性抛物型方程的窄四边形元逼近方法

讨论了一类发展方程——线性抛物型方程的窄四边形元逼近方法,导出了相应的半离散格式和全离散格式,并通过一些新的技巧,得到了相应的误差估计.     

T-optimum designs for discrimination between two multiresponse dynamic models

Summary.  The paper is concerned with a problem of finding an optimum experimental design for discriminating between two rival multiresponse models. The criterion of optimality that we use is based on the sum of squares of deviations between the models and picks up the design points for which the divergence is maximum. An important part of our criterion is an additional vector of experimental conditions, which may affect the design. We give the necessary conditions for the design and the additional parameters of the experiment to be optimum, we present the algorithm for the numerical optimization procedure and we show the relevance of these methods to dynamic systems, especially to chemical kinetic models.     

Empirical likelihood inference for the regression model of mean quality‐adjusted lifetime with censored data

The authors consider the empirical likelihood method for the regression model of mean quality‐adjusted lifetime with right censoring. They show that an empirical log‐likelihood ratio for the vector of the regression parameters is asymptotically a weighted sum of independent chi‐squared random variables. They adjust this empirical log‐likelihood ratio so that the limiting distribution is a standard chi‐square and construct corresponding confidence regions. Simulation studies lead them to conclude that empirical likelihood methods outperform the normal approximation methods in terms of coverage probability. They illustrate their methods with a data example from a breast cancer clinical trial study.     

平面电磁波在两种不同媒质中传播特性的比较

从麦克斯韦方程出发,对平面电磁波在两种不同媒质中的传播进行了具体的分析、比较,说明电磁波的传播与媒质有很大关系。     

多项式、线性方程组及范德蒙行列式的相互应用

本文试图探讨多项式、线性方程组、范德蒙行列式的相互应用,从而揭示了它们的相互关系.     

系统模型在实证经济分析中的应用介绍——以农村公共投资研究为例

社会经济实证研究在设计一项研究方案时首先要明确的三大因素是 :研究的目标 ,依据研究目标所形成的假说或者说要回答的问题 ,为实现研究目标、检验研究假说而依据的理论框架和所采用的分析方法。选择恰当的分析方法对实现研究目标以及对所获得研究结论的科学性和合理性至关重要。当某一组经济活动同时受另一组因素共同作用时 ,这些因素对该组经济活动的影响结果以及其因果关系很难独立区分 ,同时各经济变量之间具有内生性 ,在这种情况下如采用单方程模型分析就会造成模型估计结果有偏 ,因而需要采用系统模型。     

带状方程组并行列处理法贪心方法

利用列处理法贪心方法和分治策略,给出了一种求解任意相容性带状方程组的解或任意不相容性带状方程组最小二乘解的消息传递多指令流多数据流并行迭代解法,分析了解法的收敛性、计算复杂性和数值稳定性。该方法能使得各处理机上的负载基本平衡,得到了理想的加速比和并行效率。     

电流型变频调速系统动态模型研究

本文主要通过异步电动机电压矩阵方程[1],推导出异步电动机的动态结构图,然后推导出交—直—交电流型变频调速双闭环系统的动态结构图。利用该结构图,在模拟机 DMJ—313上对负载扰动进行了仿真研究。试验表明,调整调节器参数,可使负载扰动指标达到满意的要求,为在设计中选择调节器参数提供了依据。     

Efficient Estimation in Marginal Partially Linear Models for Longitudinal/Clustered Data Using Splines

Abstract.  We consider marginal semiparametric partially linear models for longitudinal/clustered data and propose an estimation procedure based on a spline approximation of the non-parametric part of the model and an extension of the parametric marginal generalized estimating equations (GEE). Our estimates of both parametric part and non-parametric part of the model have properties parallel to those of parametric GEE, that is, the estimates are efficient if the covariance structure is correctly specified and they are still consistent and asymptotically normal even if the covariance structure is misspecified. By showing that our estimate achieves the semiparametric information bound, we actually establish the efficiency of estimating the parametric part of the model in a stronger sense than what is typically considered for GEE. The semiparametric efficiency of our estimate is obtained by assuming only conditional moment restrictions instead of the strict multivariate Gaussian error assumption.