面板数据下序贯模型变点的渐近检验法

本文研究了面板数据模型下变点是否存在的检验问题.对于面板序贯模型下的变点,利用构造的检验统计量及其极限分布的方法,获得了关于变点的一种渐近检验法.随后进行Monte-Carlo数值模拟,在模拟中对检验方法的经验检验水平、检验功效以及变点后的停时三个判断标准进行了考察.结果显示无论在理论还是数值模拟上,我们提出的渐近检验法均表现优良.推广了现有文献的关于单序列变点的序贯检验方法.     

基于非参数方法的交通流变点问题分析

考虑到交通流数据的分布形式不确定及其变点数目未知的实际情形,以基于非参数方法的交通流变点问题为研究对象,拟通过基于Kolmogorov-Smirnov(KS)检验和Mann-Whitney U检验的滑动窗口法实现变点存在与否的检验,进一步结合二分法对交通流数据变点数目及其位置进行估计.正态分布模拟仿真显示,两种方法对于均值变点检验和估计效果较好,而对于方差变点检验和估计,Mann-Whitney U方法不及K-S方法.最后,贵阳市中心道路车流量数据实例分析,表明方法对于交通流突变分析效果较好,可为相关部门提供可靠的决策依据.     

高维纵向数据群点的刚体结构检验方法

本文中, 我们提出一种检验高维纵向数据群点在运动中是否保持刚体结构的方法, 并给出高维群点变形系数的定义. 对群点刚体结构的检验, 可以把握群点运动的主要特征, 并便于对群点的未来运动趋势做总体预测. 通过仿真案例以及分析比较中国东部、西部城市群的经济发展过程中多元性的变化, 验证了方法的合理性和应用价值.     

含尺度变点稳定分布的单位根检验

研究稳定分布噪声模型中含有尺度变点的单位根检验问题.在尺度突变的情形下,给出DF型检验统计量在原假设成立时的渐近分布.结果表明:统计量的渐近分布不仅是Lévy过程的泛函,且依赖尺度变化的位置和跳跃幅度.最后,通过Mente Carlo数值模拟证实,DF检验统计量不再稳健,尺度变点会导致单位根检验的经验水平值发生扭曲.     

转点识别的稳定性

将假设检验的稳定性[1]引入到转点识别中来,考虑了转点识别在正态假设下的稳定性问题.结果显示,转点的N-P检验稳定性不很理想.     

基于自正则的K-S方法对QFII羊群行为的变点检验

基于自正则的K-S方法对2005年第1季度至2011年第4季度QFII羊群行为的均值变点进行检验,发现QFII在中国A股市场上羊群行为度序列确实存在均值变点,QFII羊群行为发生变化的时点分别为2007年第3季度与2009年第4季度.与传统的Kolmogorov-Smirnov检验以及"滑窗"检验方法相比,基于自正则的K-S检验可以避免长程方差的相合估计与窗宽参数的选取.在检验小样本容量数据时,比传统的K-S检验更加适用。     

基于Bootstrap的厚尾相依序列持久性变点检验

基于修正方差比率函数给出一种检验厚尾序列持久性变点的统计量.在无变点的假设下得到了统计量的渐近分布.为避免检验渐近分布中的厚尾指数,构造Bootstrap抽样方法来确定渐近分布的经验临界值.数值模拟研究结果说明修正方差比率统计量及Bootstrap抽样方法的有效性.     

非参数回归中方差变点的小波检测(英文)

本文主要研究了非参数回归模型中方差函数的变点, 利用小波方法构造的检验量来检测方差中的变点,建立了这些检验量的渐近分布, 并且运用这些检验量构造了方差变点的位置和跳跃幅度的估计, 给出了这些估计的渐近性质, 并进一步通过随机模拟验证了本文方法在有限样本下的性质.     

基于经验似然的Logistic回归模型的变点检验

基于经验似然对Logistic回归模型进行变点检验及估计.通过建立变点模型,构造经验对数似然比统计量,在大样本下,证明了经验对数似然比统计量与经典参数对数似然比统计量具有相同的极值分布,同时得到变点的估计及估计的相合性,并通过数值模拟及实例说明经验似然方法检验变点的可行性.     

部分线性模型非参数分量的线性关系检验

对于部分线性模型中非参数部分是否为某一特定阶数(记为p)的多项式函数的检验问题,本文基于非参数函数在各点的p阶导函数估计值的样本方差构造了一个简单的检验统计量.给出了计算检验p-值的三阶矩χ2逼近方法.最后通过数值模拟验证了我们所提检验方法的有效性.     

Arguing About the Effectiveness of Assessments for the Classroom

Approaches to test score use and test purpose lack the well-developed methodological guidelines and established sources of evidence available for intended score interpretation. We argue in this paper that this lack fails to reflect the ultimate purpose of a test score—to help solve an important problem faced by intended test users. We explore the treatment of intended test purpose and test score use under the chain of assumption/inferences perspective identified within an argument-based approach to validity. Next, we revisit the notion of test score use and argue that, at least for classroom assessments based on complex constructs, such as learning progressions in math and science, test score use can be more effectively conceptualized as part of a potential solution to solving a problem, or “job-to-be-done.”. We argue for shifting from the definition of validity to the concept of effectiveness. Finally, we illustrate an argument- based approach to test score effectiveness by contrasting effectiveness arguments for interim assessments based on a conventional test blueprint or a test blueprint augmented with learning progressions.     

血样二次分组检验的探讨

提出了血样的二次分组检验方法,建立了二次分组验血法预期人均检验次数最小的模型,给出了二次分组法的最佳小组人数和最佳小组数的范围,得到了求二次分组最佳方案的方法.计算结果表明模型和方法是可信的,在单个人血样呈阴性概率较大时,采用二次分组验血法能比一次分组验血法更进一步地减少检验次数,有较大的实用价值.     

试卷水平的标准化定量评价

通过建立一个实用标准化评价模型,根据转换参数(偏移参数和膨胀参数)给出试卷水平的标准化评价,并对其做Kappa一致性检验.Kappa系数K作为试卷水平系数.X~2一致性检验和理想模式比较检验从不同角度验证了标准化评价的有效性.给出了两个样本组的实证分析.     

Empirical likelihood based goodness-of-fit testing for generalized linear mixed models

In this paper, we propose a bias-corrected empirical likelihood （BCEL） ratio to construct a goodness- of-fit test for generalized linear mixed models. BCEL test maintains the advantage of empirical likelihood that is self scale invariant and then does not involve estimating limiting variance of the test statistic to avoid deteri- orating power of test. Furthermore, the bias correction makes the limit to be a process in which every variable is standard chi-squared. This simple structure of the process enables us to construct a Monte Carlo test proce- dure to approximate the null distribution. Thus, it overcomes a problem we encounter when classical empirical likelihood test is used, as it is asymptotically a functional of Gaussian process plus a normal shift function. The complicated covariance function makes it difficult to employ any approximation for the null distribution. The test is omnibus and power study shows that the test can detect local alternatives approaching the null at parametric rate. Simulations are carried out for illustration and for a comparison with existing method.     

“正项级数收敛性的一种新的判别法”的注记

给出了标题中所述文章的一个注记.首先否定了该文中的一个断语,其次指出了该文中的"新的判别法"的适用范围并没有超过Cauchy根值判别法.     

Test elements of direct sums and free products of free Lie algebras

We give a characterization of test elements of a direct sum of free Lie algebras in terms of test elements of the factors. In addition, we construct certain types of test elements and we prove that in a free product of free Lie algebras, product of the homogeneous test elements of the factors is also a test element.     

A test of conditional heteroscedasticity in time series

A new test of conditional heteroscedasticity for time series is proposed. The new testing method is based on a goodness of fit type test statistics and a Cramer-von Mises type test statistic. The asymptotic properties of the new test statistic is establised. The results demonstrate that such a test is consistent. Project supported by the National Natural Science Foundation of China (Grant No. 19231050) and Postdoctoral Fund of China.     

Planning accelerated life tests with random effects of test chambers

In accelerated life tests (ALTs), test units are often tested in multiple test chambers along with different stress conditions. The nonhomogeneity of test chambers precludes the complete randomized experiment and may affect the life‐stress relationship of the test product. The chamber‐to‐chamber variation should be taken into account for ALT planning so as to obtain more accurate test results. In this paper, planning ALTs under a nested experimental design structure with random test chamber effects is studied. First, by a 2‐phase approach, we illustrate to what extent different test chamber assignments to stress conditions may impact the estimation of unknown parameters. Then, D‐optimal test plans with 2 test chambers are considered. To construct the optimal design, we establish the generalized linear mixed model for failure‐time data and apply a quasi‐likelihood method, where test chamber assignments, as well as other decision variables that are required for planning ALTs, are simultaneously determined.     

Post-J test inference in non-nested linear regression models

This paper considers the post-J test inference in non-nested linear regression models. Post-J test inference means that the inference problem is considered by taking the first stage J test into account. We first propose a post-J test estimator and derive its asymptotic distribution. We then consider the test problem of the unknown parameters, and a Wald statistic based on the post-J test estimator is proposed. A simulation study shows that the proposed Wald statistic works perfectly as well as the two-stage test from the view of the empirical size and power in large-sample cases, and when the sample size is small, it is even better. As a result,the new Wald statistic can be used directly to test the hypotheses on the unknown parameters in non-nested linear regression models.     

A generalized Hollander-Proschan type test for NBUE alternatives

In this note we develop a family of test statistics for testing exponentiality against NBUE alternatives. The asymptotic distribution of the test statistics is derived. The test statistics are shown to be asymptotically normal and consistent. This family of test statistics includes the test proposed by Hollander and Proschan (1975) as a special case. Efficiency studies have also been done.