Imposing and Testing for Shape Restrictions in Flexible Parametric Models

In many economic models, theory restricts the shape of functions, such as monotonicity or curvature conditions. This article reviews and presents a framework for constrained estimation and inference to test for shape conditions in parametric models. We show that “regional” shape-restricting estimators have important advantages in terms of model fit and flexibility (as opposed to standard “local” or “global” shape-restricting estimators). In our empirical illustration, this is the first article to impose and test for all shape restrictions required by economic theory simultaneously in the “Berndt and Wood” data. We find that this dataset is consistent with “duality theory,” whereas previous studies have found violations of economic theory. We discuss policy consequences for key parameters, such as whether energy and capital are complements or substitutes.     

Indirect membership function assignment based on ordinal regression

In many fuzzy sets applications, fuzzy membership functions are commonly developed based on empirical or expert knowledge. The equation of a membership function is usually determined somewhat arbitrarily. This paper explores a novel membership function design method based on ordinal regression analysis. The estimated thresholds between ordinal measurement categories are applied to calculate the intersection points between fuzzy sets. These intersection points are further applied to determine the equations of the membership functions. Information distortion due to empirical guess can thus be reduced and more latent information in the fuzzy responses can therefore be captured. A case study investigating the relationship between foster mothers’ satisfaction and the foster time and information provided has been conducted in this research. The applicability and effectiveness of the proposed membership function assignment approach have been demonstrated through several case studies.     

Bayesian estimation and influence diagnostics of generalized partially linear mixed-effects models for longitudinal data

This paper develops a Bayesian approach to obtain the joint estimates of unknown parameters, nonparametric functions and random effects in generalized partially linear mixed models (GPLMMs), and presents three case deletion influence measures to identify influential observations based on the φ-divergence, Cook's posterior mean distance and Cook's posterior mode distance of parameters. Fisher's iterative scoring algorithm is developed to evaluate the posterior modes of parameters in GPLMMs. The first-order approximation to Cook's posterior mode distance is presented. The computationally feasible formulae for the φ-divergence diagnostic and Cook's posterior mean distance are given. Several simulation studies and an example are presented to illustrate our proposed methodologies.     

A Proportional Hazards Regression Model for the Subdistribution with Covariates‐adjusted Censoring Weight for Competing Risks Data

With competing risks data, one often needs to assess the treatment and covariate effects on the cumulative incidence function. Fine and Gray proposed a proportional hazards regression model for the subdistribution of a competing risk with the assumption that the censoring distribution and the covariates are independent. Covariate‐dependent censoring sometimes occurs in medical studies. In this paper, we study the proportional hazards regression model for the subdistribution of a competing risk with proper adjustments for covariate‐dependent censoring. We consider a covariate‐adjusted weight function by fitting the Cox model for the censoring distribution and using the predictive probability for each individual. Our simulation study shows that the covariate‐adjusted weight estimator is basically unbiased when the censoring time depends on the covariates, and the covariate‐adjusted weight approach works well for the variance estimator as well. We illustrate our methods with bone marrow transplant data from the Center for International Blood and Marrow Transplant Research. Here, cancer relapse and death in complete remission are two competing risks.     

基于自组织的大型建筑企业控制力协同进化研究

针对大型建筑企业控制力动态协同的定量化仿真问题,基于复杂系统视角,应用自组织理论分析大型建筑企业控制力自组织耦合网络作用关系,选择有效朗之万方程构建大型建筑企业控制力系统的自组织协同进化模型,通过线性近似法的性态稳定求解非线性方程的稳定性,得出大型建筑企业控制力系统协同进化演化过程的四个决定性参数,并通过MATLAB软件进行参数枚举取值,具体分析企业控制力协同演化。案例验证该模型可对大型建筑企业控制力协同演化最佳状态实现更加精确的参数取值,并发现大型建筑企业控制力协同演化最佳状态的充要条件,以及一种新的大型建筑企业控制力协同演化状态。     

综合评价中一种凹性指数型功效函数

目前主流功效函数多为凸性,在处理社会经济数据集中常见的右偏样本时效果难以令人满意。通过系统探讨凸性和凹性功效函数各自的适用特征,指出凹性函数在应用中有其必要性。归纳并使用偏度、区分度、P-P图三种方法作为分布形态的评判标准,比较了常见功效函数对指标原始数据分布形态的调整作用。在分析基础上,提出一种改进的凹性指数功效函数,能有效地处理右偏数据,且相比使用对数预处理的凸性功效函数更具适用性与便利性。     

中国工业要素替代弹性的分解——基于直接替代效应和诱致性技术创新效应的研究

基于固定替代弹性(CES)生产函数构建了要素替代弹性分解的理论框架模型,根据技术进步是否发生改变,将要素替代弹性分解为直接替代效应和诱致性技术创新效应,并利用1978—2013年中国工业数据对其进行了实证检验分析。实证结果表明:在中国工业化进程中,中国工业资本与劳动之间是呈互补关系;同时,在要素替代过程中,诱致性技术创新效应起到了主要作用。因此,在中国经济转型的新常态下,应该继续加大技术创新的投入力度,加速推进工业产业技术升级,优化产业结构。     

新时代社会主义意识形态的功能提升研究

意识形态功能是意识形态基础研究的核心问题,从意识形态功能提升视角切入是推进我国社会主义意识形态建设的新视阈。在意识形态功能的研究中,抛开时代背景和具体实践谈功能,极易出现意识形态功能研究的“虚化”,形成对意识形态功能的空洞认识。在新时代的历史方位下,结合习近平新时代中国特色社会主义思想论证社会主义意识形态在政治、经济、文化、社会和外交领域的相关功能,以期在市场化、“微时代”、全球化的大环境下通过引领社会主义市场经济改革方向、净化网络空间以及争夺国际话语权等途径,真正实现社会主义意识形态功能的全面提升。     

湖南沅江话“持续/进行体”的表达形式

对沅江话中五种"持续/进行体"的表达形式进行描写和分析,发现沅江话中主要通过在动词后加助词"着/哒/起"来表示各种持续或进行的意义,缺少普通话中于动词前加副词"正在/在"表示进行的方式。这五种形式及其具体意义分别是:表示暂且/短暂持续的"V下着、V哒(O)着";表示事物存在状态或行为伴随状态的持续的"一V起、V1起(O)V2";表示动作行为或存在状态或行为伴随状态的持续的"V哒O、V1哒(O)V2";表示动态行为的持续的"V餐V餐…、V餐(O)";表示动态行为的持续与进行的"在咯里/哦里+V"。