Generalized empirical likelihood inference in partially linear model for longitudinal data with missing response variables and error-prone covariates

In this article, we consider statistical inference for longitudinal partial linear models when the response variable is sometimes missing with missingness probability depending on the covariate that is measured with error. A generalized empirical likelihood (GEL) method is proposed by combining correction attenuation and quadratic inference functions. The method that takes into consideration the correlation within groups is used to estimate the regression coefficients. Furthermore, residual-adjusted empirical likelihood (EL) is employed for estimating the baseline function so that undersmoothing is avoided. The empirical log-likelihood ratios are proven to be asymptotically Chi-squared, and the corresponding confidence regions for the parameters of interest are then constructed. Compared with methods based on NAs, the GEL does not require consistent estimators for the asymptotic variance and bias. The numerical study is conducted to compare the performance of the EL and the normal approximation-based method, and a real example is analysed.     

Pairwise comparisons of treatments with ordinal responses in a two-way setting

In clinical studies, pairwise comparisons are frequently performed to examine differences in efficacy between treatments. The statistical methods of pairwise comparisons are available when treatment responses are measured on an ordinal scale. The Wilcoxon–Mann–Whitney test and the latent normal model are popular examples. However, these procedures cannot be used to compare treatments in parallel groups (a two-way design) when overall type I error must be controlled. In this paper, we explore statistical approaches to the pairwise testing of treatments that satisfy the requirements of a two-way layout. The results of our simulation indicate that the latent normal approach is superior to the Wilcoxon–Mann–Whitney test. Clinical examples are used to illustrate our suggested testing methods.     

固定资产投资与国内生产总值的误差修正模型研究

运用协整理论和误差修正模型研究固定资产投资和国内生产总值之间的关系,可以发现它们之间存在长期均衡的协整关系,使用误差修正模型比普通的单变量方程更能反映两者长期和短期的关系,还可以避免谬误回归问题。     

用牛顿环实验测量凸透镜曲率半径的误差分析

对牛顿环测量凸透镜曲率半径实验中的误差进行了理论分析和半定量分析,指出了误差的主要来源及相应的处理方法.对于测量曲率半径P>lm的平凸透镜,公式R=Dm2-Dn2/4（m-n）λ的理论相对误差小于10-8;逐差法可以消除形变带来的系统误差;由于形变的影响应从第5级以后开始计数,对于R>1m的凸透镜要得到小于10-3的相对误差,级数应小于50,级数差值应大于30.钠光灯作为光源的系统相对误差为7.1×10-4.     

中国创新活动和经济增长的关系——一个基于协整理论的初步研究

内生经济增长理论告诉我们,创新活动作为技术进步的主要来源能够持续推动经济增长。但是中国现阶段经济发展条件下创新对经济增长的推动作用到底有多大,创新活动对于经济增长的影响机制如何,现有的研究并没有给出一个令人信服的答案。本文采用协整理论和误差修正模型研究了经济增长和创新活动之间的关系。研究结果显示,我国创新活动对于经济增长短期内具有显著影响,但其影响程度与长期影响相比还存在着较大差距;从长期看各种创新活动中基础研究能够实现对经济增长更大的推动作用。     

货运与经济发展协整关系的实证分析

应用协整方法研究我国交通运输系统规模与宏观经济发展之间的动态关联,对于把握交通系统的发展方向,合理规划交通系统,并使其与经济的发展相适应,具有重要意义。应用协整方法分析、检验了我国货运规模与经济发展之间的协整关系,定量分析了主要相关因素对货运发展的影响,建立了描述货运周转量由短期波动向长期均衡调整的动态过程的误差修正模型。分析结果表明,我国货运周转量与工业生产总值和运价之间存在唯一的长期稳定关系,短期预测模型不仅具有令人满意的拟合效果和预测能力,而且结构具有稳定性。     

住房价格上涨与其影响因素之间的关系研究——基于VEC模型的实证分析

通过建立向量误差修正模型,对中国近年来住房价格持续上涨的原因进行了分析。结果表明,土地价格的快速上涨、金融对房地产业的过度支持以及在住房价格继续上涨预期刺激下的投机因素是中国住房价格上涨过快的主要原因。近年来中国住房价格的持续快速上涨在很大程度上是一种泡沫现象。     

Comparison of procedures for fitting the autoregressive order of a vector error correction model

This paper investigates the lag length selection problem of a vector error correction model by using a convergent information criterion and tools based on the Box–Pierce methodology recently proposed in the literature. The performances of these approaches for selecting the optimal lag length are compared via Monte Carlo experiments. The effects of misspecified deterministic trend or cointegrating rank on the lag length selection are studied. Noting that processes often exhibit nonlinearities, the cases of iid and conditionally heteroscedastic errors will be considered. Strategies that can avoid misleading situations are proposed.     

走出广告言辞表达的误区

〕本文着重对言辞表达不当导致广告误区的问题作出分析,并认为除语言本体的规范标准外,还必须用汉语文化精神和民族精神的尺度,去对广告言辞的是非优劣作出评判。