Testing inequality constraints in a linear regression model with spherically symmetric disturbances

This paper develops a Wald statistic for testing the validity of multivariate inequality constraints in linear regression models with spherically symmetric disturbances, and derive the distributions of the test statistic under null and nonnull hypotheses. The power of the test is then discussed. Numerical evaluations are also carried out to examine the power performances of the test for the case in which errors follow a multivariate student-t （Mt） distribution.     

DESIGNING THE OPTIMUM CONFIGURATIONS OF CIRCULAR AND SPHERICAL PRODUCT SPECIFICATIONS FOR MULTIPLE QUALITY CHARACTERISTICS

1. Introduction The problem of determining an optimal tolerance is equivalent to the problem of determining optimal specification limits, since the term tolerance refers to the distance between its lower and upper specification limits. Functional performance and economic considerations are the two primary factors affecting the design of tolerances. A tighttolerance usually implies high manufacturing cost due to additional manufacturing operations, slow processing rates, additional care on part…     

嵌套Logistic模型的矩估计

讨论多元极值分布嵌套 Logistic模型 ,给出了分布参数的矩估计及其渐近协方差阵元素的显式表示和数值结果 .当边缘参数相等时 ,用合并样本估计公共参数 ,可以提高估计量的精度 .     

Bayes多元时间序列分析方法及其应用

在条件似然函数意义下,讨论了基于矩阵正态-Wishart分布的多元时间序列Bayes分析方法,得到了模型参数的后验分布与一步预测分布.给出了分量方程的对应结果,说明了模型阶数的推断方法.最后,列出了计算步骤,并作为应用,对上海房地产价格指数数据进行预测建模,取得了较好效果.     

基于高斯混合模型的光纤罗经误差概率分布建模

针对船用光纤罗经误差的概率分布不完全符合高斯分布的情况, 提出了一种基于高斯混合模型(Gaussian mixture model, GMM)的光纤罗经误差概率分布函数(probability distribution function, PDF)建模方法。该方法使用多个高斯分布的线性叠加来拟合光纤罗经误差的概率分布, 并结合一种鲁棒性的期望最大化(expectation maximization, EM)算法来估计GMM中的参数。仿真分析和实测数据验证, 相比于使用单一的高斯分布, 基于所提方法建立的光纤罗经误差概率分布更加符合该导航设备误差的实际概率分布。     

The Queue Length Distribution for M/G/1 Queue with Delay Single Server Vacation

1　IntroductionDuringrecentseveraldecadesmanyauthorsstudiedM/G/1queueswithdifferentservervacationregimes(seeRefs.[1～6]).Theynotonlystudiedthestochasticdecompositionpropertiesofthequeuelengthandwaitingtimewhenthesystemisinequilibrium,butalsostudiedthetransientandequilibriumdistributionsofthequeuelength.InRef.[6]theau-thorsstudiedM/G/1queuewithdelaymultipleservervacationsinwhichtheserverhasthreestates:vacation-preparation,vacationandbusyperiod.InthispaperwefirstdiscusstheM/G/1queuewithdelay…     

Empirical likelihood for longitudinal partially linear model with α-mixing errors

This paper considers large sample inference for the regression parameter in a partially linear regression model with longitudinal data and α-mixing errors. The authors introduce an estimated empirical likelihood for the regression parameter and show that its limiting distribution is a mixture of central chi-squared distributions. Also, the authors derive an adjusted empirical likelihood method which is shown to have a central chi-square limiting distribution. A simulation study is carried out to assess the performance of the empirical likelihood method.     

对数正态分布下的模糊维修性指标验证方法

基于维修性指标验证在提高武器系统费效比中的重要性,针对常用的对数正态分布,提出了一种模糊维修性指标验证方法。在样本数据精确,统计假设模糊的情形,以控制出现两类错误的概率为目的,研究了对数正态分布下的模糊假设检验问题。实例表明该方法能有效处理维修时间服从对数正态分布时,具有模糊背景的平均修复时间的模糊假设检验问题,对装备试验靶场进行维修性试验与鉴定具有借鉴意义。     

THE GOODNESS-OF-FIT TEST BY USING MULTIVARIATE RANDOM WEIGHTING METHOD

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基于多元条件极值模型的股指期货与现货下尾部相依性研究

运用多元条件极值模型研究了沪深300股指期货与现货指数之间的下尾部相依关系。通过先构建随机波动-超阈值（SV-POT）模型描述两种资产收益的边缘分布，再建立多元条件极值模型对分布下尾部的相依结构进行研究。实证结果表明：两个收益的下尾存在显著为正的相依关系且条件相依程度都在80%以上，但相差不大，两者可以看成是一个同质的市场。     

Bayesian empirical likelihood estimation of quantile structural equation models

Structural equation model (SEM) is a multivariate analysis tool that has been widely applied to many fields such as biomedical and social sciences. In the traditional SEM, it is often assumed that random errors and explanatory latent variables follow the normal distribution, and the effect of explanatory latent variables on outcomes can be formulated by a mean regression-type structural equation. But this SEM may be inappropriate in some cases where random errors or latent variables are highly nonnormal. The authors develop a new SEM, called as quantile SEM (QSEM), by allowing for a quantile regression-type structural equation and without distribution assumption of random errors and latent variables. A Bayesian empirical likelihood (BEL) method is developed to simultaneously estimate parameters and latent variables based on the estimating equation method. A hybrid algorithm combining the Gibbs sampler and Metropolis-Hastings algorithm is presented to sample observations required for statistical inference. Latent variables are imputed by the estimated density function and the linear interpolation method. A simulation study and an example are presented to investigate the performance of the proposed methodologies.     

基于多变量经验概率模型的中国粮食产量模拟预测分析

基于多变量经验概率模型(MVE)设定了A和B两个模拟方案对我国粮食产量进行模拟预测, 并运用绝对误差均值(MAE)、均方根误差(RMSE)、误差相对比(MAPE)和希尔不等式系数(Theil IC)对模拟结果的预测精度进行了检验. 结果表明, 多变量经验概率模型的短期模拟预测精度较好, 且模拟运用的历史数据时间间隔越短, 模拟预测精度越高; 根据2000-2008年的历史数据(B方案)和多变量经验概率模型模拟得到的2010年和2011年我国粮食产量的模拟均值分别为53288万吨和53887万吨, 标准差分别为1967万吨和2001万吨.     

An M/G/1 Queueing System with Delay Server Vacations

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基于厚尾分布的非寿险准备金评估模型

未决赔款准备金评估是财产保险公司偿付能力管理的核心工作,通常使用的评估方法是广义线性模型.当增量赔款数据存在尖峰厚尾特征时,广义线性模型的传统分布假设可能与实际数据不相符合.此外,保险公司的多条业务线之间往往存在一定的相依关系,这就要求对总准备金的评估结果进行相应调整.本文使用三种新的厚尾分布(即幂Frechet分布、广义对数Moyal分布和全尾伽马分布)代替传统模型中使用的伽马分布、对数正态分布和GB2分布假设,考察它们在未决赔款准备金评估中的应用效果,并应用Copula函数描述了不同业务线之间的相依关系.借助参数化bootsrap和蒙特卡罗随机模拟方法,给出了准备金的预测分布和风险度量值.基于一组实际数据的研究结果表明,厚尾分布对于改善未决赔款准备金的预测效果具有很高的应用价值,而相依性的调整也使得准备金的预测结果更加合理.     

STRONGLY CONSISTENT ESTIMATION FOR A MULTIVARIATE LINEAR RELATIONSHIP MODEL WITH ESTIMATED COVARIANCES MATRIX

1 IntroductionSuppose that the true values Of a set of variables satisfy exact linear relationships, but theyare unobserved. We can Obtain the Observed values which are the sums of the true values anderrors of measurement. The model is described as follows. A set of rmdimensional vectors {xh}satisfyB'xk or = 0, k = 1,2,'' t (1.1)where B is an m x p parameter mains with rank p < m and o is a p x 1 parameter vector. Weobserved {Zk}, which are m x 1 random vectors and satisfyZk = ac ed, …     

Optimization of Additively Decomposed Function with Constraints

We propose a modified evolutionary computation method to solve the optimization problem of additively decomposed function with constraints, ft is based on factorized distribution instead of penalty function and any transformation to a linear model or others. The feasibility and convergence of the new algorithm are given. The numerical results show that the new algorithm gives a satisfactory performance.     

基于可靠性增长的变总体可靠性试验鉴定方法

针对产品研制过程中存在多阶段的试验数据和产品性能参数呈现可靠性增长的特点, 提出了一种变总体可靠性试验鉴定方法. 该方法依据产品研制过程中不同总体的试验数据, 利用可靠性增长模型, 给出变总体试验信息似然比的定义和判决准则, 进而给出变总体可靠性试验鉴定方法. 通过实例对比分析, 该方法可较好地解决小子样产品可靠性指标的假设检验问题.     

随机波动率模型的参数估计及对中国股市的实证

基于有效重要性抽样(EIS)技巧,提出极大似然(ML)方法估计了四种不同收益分布假定的随机波动率(SV)模型的参数. 以上证综合指数和深证成份指数为例,实证检验了不同收益分布假定的SV模型的性能,分析适合我国股票市场的SV模型及收益分布. 实证结果表明,与正态分布、学生t-分布和广义误差分布(GED)假定的SV模型相比,具有“有偏”和“尖峰厚尾”特征的有偏学生t-分布假定的SV (SVSKt)模型能够更好地描述中国股票市场的波动性.     

线性回归模型的非线性稳健估计——基于经验过程理论的研究

线性回归模型参数估计的有效性及对厚尾扰动和离群值的稳健性有进一步改进的余地.本文基于条件分布函数提出线性参数模型的一种新的非线性稳健估计量,利用经验过程理论证明了其相合性和渐近正态性.相对于OLS(ordinary least squares)估计量和常用的稳健LAD(least absolute deviations)和Huber估计量,此估计量可全面把握因变量的分布信息,较准确地由样本数据反映真正的数据生成过程,关于扰动项的厚尾分布具有更好的稳健性,且可更好地消弱极端离群值样本对参数估计的不良影响.多种实验设计的模拟表明,此估计量在有限样本下表现良好;在厚尾扰动或离群值出现的时候,显示出良好的稳健性,且优于OLS、LAD以及Huber估计量的小样本表现.     

有偏胖尾分布下的金融市场风险测度方法

通过对上证综指和世界股市若干重要指数收益的统计特征分析发现,无论是成熟资本市场还是新兴资本市场,其收益分布都展现出较为显著的“有偏”和“尖峰胖尾”特征,因此,主流金融理论假定的正态分布或对称学生分布都无法全面准确刻画股市收益的真实分布特征和风险状况。通过引入有偏的学生分布,分析和对比了不同收益分布假定下的市场波动率和风险价值计算方法,并利用风险价值的失败率似然比检验以及动态分位数回归检验法,实证分析了不同分布模型的适用范围和精确程度,探讨了非正态分布假定下的金融市场风险测度方法。