微分方程的解关于部分变元的弱吸引性

本文提出关于部分变元的弱吸引及其相关概念,并给出判定他们的充分条件。文献[]、[]中的相应结果可作为本文的特例。12     

集成电路中布尔线路图的优化设计

二叉决策图（BDDs)是布尔函数的一个表示方法,最近它被广泛应用于逻辑综合中布尔电路的模拟和测试等领域。在这些应用中,有些基本问题需要解决,其中包括电路图到决策图的转换。文章提出了一个转换的方法并分两步叙述,首先是对无扇出电路的转换,然后是对有扇出电路的转换,最后把两者结合为一个通用算法。     

基于非参数回归的遗漏变量检验

基于非参数回归提出了同时适用于横截面和时间序列数据的遗漏变量检验统计量.与现有文献相比,该统计量不仅避免了模型设定偏误问题,而且具有更高的局部检验功效,能够识别出速度更快的收敛到原假设的局部备择假设.该文选择单一带宽估计条件联合期望和条件边际期望,允许二者的非参数估计误差共同决定统计量的渐近分布,不仅改善了统计量的有限样本性质,而且避免了选择多个带宽和计算多个偏差项产生的繁杂工作.蒙特卡洛模拟结果表明该统计量具有良好的有限样本性质以及比Ait-Sahalia等更高的检验功效.实证分析采用该统计量捕获了F统计量无法识别的产出缺口与通胀之间关系,验证了非线性“产出一通胀”型菲利普斯曲线在中国的适用性.     

带有潜变量的结构方程模型在突发事件应急管理中的应用

如何使事件与机构挂钩是突发事件应急管理中的一个重要问题;通过带有潜变量的结构方程模型能够建立起事件与机构之间的定量联系,从而为进一步对机构作评价和制定考核标准提供依据。     

Estimation of population distribution function involving measurement error in the presence of non response

Abstract

This article addresses the problem of estimating population distribution function for simple random sampling in the presence of non response and measurement error together. We suggest a general class of estimators for estimating the cumulative distribution function using the auxiliary information. The expressions for the bias and mean squared error are derived up to the first order of approximation. The performance of the proposed class of estimators is compared with considered estimators both theoretically and numerically. A real data set is used to support the theoretical findings.     

社会保险成本过高是否抑制企业投资?

社会保险成本过高是否抑制企业投资，从而阻碍实体经济发展?对此，文章利用工业企业微观数据实证检验了企业社保成本变动对投资率的影响.为缓解内生性问题，文章选择城市老年人比重作为工具变量.实证检验显示企业社保支出比重增加1个单位标准差，企业投资率约下降3.3%，能够解释企业投资率变动的6.4%，具有较强经济显著性.文章还探究了社保成本变动影响企业投资的内在机制，发现劳动成本渠道、生产率渠道以及融资约束渠道都得到相关经验证据的支持.研究结果说明降低企业社保成本的政策如果能够得到有效落实，将会刺激企业扩大投资，促进地区经济发展.     

Improved methods for moment restriction models with data combination and an application to two-sample instrumental variable estimation

Combining-100 information from multiple samples is often needed in biomedical and economic studies, but differences between these samples must be appropriately taken into account in the analysis of the combined data. We study the estimation for moment restriction models with data combined from two samples under an ignorability-type assumption while allowing for different marginal distributions of variables common to both samples. Suppose that an outcome regression (OR) model and a propensity score (PS) model are specified. By leveraging semi-parametric efficiency theory, we derive an augmented inverse probability-weighted (AIPW) estimator that is locally efficient and doubly robust with respect to these models. Furthermore, we develop calibrated regression and likelihood estimators that are not only locally efficient and doubly robust but also intrinsically efficient in achieving smaller variances than the AIPW estimator when the PS model is correctly specified but the OR model may be mispecified. As an important application, we study the two-sample instrumental variable problem and derive the corresponding estimators while allowing for incompatible distributions of variables common to the two samples. Finally, we provide a simulation study and an econometric application on public housing projects to demonstrate the superior performance of our improved estimators. The Canadian Journal of Statistics 48: 259–284; 2020 © 2019 Statistical Society of Canada     

Some imputation methods to compensate with non-response for estimation of population mean in two-occasion successive sampling

Abstract

Non-response is an unavoidable phenomenon in almost all sample survey, and if it is not dealt carefully at the very starting of the analysis, results may lead to significant biases in the survey estimates. Keeping these facts in mind and inspired by the work of Singh (2009 Singh, S. 2009. A new method of imputation in survey sampling. Statistics 43 (5):499–511. doi:10.1080/02331880802605114.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]), this article suggests some alternative efficient methods to deal with the missing data problems at the beginning of the analysis and proposes estimation procedures of the current population mean in two-occasion successive sampling. The properties of the resultant estimation procedures have been examined and supplemented with empirical studies. Results have been critically analyzed, and recommendations are made to the survey practitioners.     

On weighted Renyi’s entropy for double-truncated distribution

In a recent paper, Nourbakhsh and Yari (2017 Nourbakhsh, M., and G. Yari. 2017. Weighted Renyi’s entropy for lifetime distributions. Communications in Statistics—Theory and Methods 46 (14):7085–98.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) introduce the weighted version of Renyi’s entropy for left/right truncated random variables and studied their properties in context of reliability analysis. In the present communication we extend the notion of weighted Renyi’s entropy for two-sided truncated random variable. In reliability theory and survival analysis, this measure may help to study the quantitative-qualitative information spectrum of a system/component when it fails between two time points. Various aspects of weighted Renyi’s interval entropy have been discussed and some mistakes in the preceding literature have also been corrected. These results generalize and enhance the related existing results that are developed based on weighted Renyi’s entropy for one-sided truncated random variable. Finally, a simulation study is added to provide the estimates of the proposed measure and to demonstrate the performance of the estimates.     

Estimation of population mean in successive sampling under super-population model in presence of random non response situations

The present work is an attempt to estimate the population mean on the current occasion in two-occasion successive (rotation) sampling in presence of random non response situations. The estimation strategy has been constructed under a super-population model design approach with the help of imputation technique. The estimators proposed on the current occasion cover the cases of occurrences random non responses on either of the occasions. Detail behaviors of the proposed class of estimators have been studied and its performance has been examined with the sample mean estimator. The results are demonstrated through empirical studies which establish the effectiveness of the proposed class of estimators. Suitable recommendations have been put forward to the survey statisticians for its practical application.