一基于SEM的经济发展与社会发展关系——以济南市为例

利用济南市2001—2013年的数据,构建济南市经济与社会发展关系的结构方程模型(SEM),考量经济发展的4个潜变量(经济水平、经济结构、经济增速、经济物耗)与社会发展的4个潜变量(居民的生活质量、社会稳定、人口素质、生态环境)间的相互影响,结果表明,居民生活质量正相关于人口素质和经济水平,人口素质正相关于经济水平;居民生活质量作用于社会稳定,而社会稳定是生活质量的固有要求;生态环境负相关于经济增速和经济物耗。     

改进离散人工蜂群算法规划异形满版服饰图案切割路径

服饰图案切割路径规划是服饰图案自动切割技术的关键部分之一。文中用改进的离散人工蜂群算法实现了激 光切割系统对异形满版服饰图案的切割工艺路径规划优化。首先,把满版服饰图案激光切割路径规划转化为广义旅行 商问题求解,证明了路径规划转化成普通TSP问题比转化成第一类广义TSP问题更为有效,并给出了路径规划中“图案 始切割点”的优化选择方法。然后结合部分匹配交叉和启发式变异搜索方法的人工蜂群算法求解TSP问题,证明了与 A*算法及遗传算法相比,该方法更为优越。并且该方法已应用于激光切割机切割异形满版服饰图案路径规划的生产实 践,运行可靠,比未规划时的工艺路线平均提高效率33.7%。该方法提供了一种解决TSP问题的新方法,具有一定的理 论意义和价值     

Influence diagnostics for the Weibull-Negative-Binomial regression model with cure rate under latent failure causes

In this paper, we propose a flexible cure rate survival model by assuming that the number of competing causes of the event of interest follows the Negative Binomial distribution and the time to event follows a Weibull distribution. Indeed, we introduce the Weibull-Negative-Binomial (WNB) distribution, which can be used in order to model survival data when the hazard rate function is increasing, decreasing and some non-monotonous shaped. Another advantage of the proposed model is that it has some distributions commonly used in lifetime analysis as particular cases. Moreover, the proposed model includes as special cases some of the well-know cure rate models discussed in the literature. We consider a frequentist analysis for parameter estimation of a WNB model with cure rate. Then, we derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and present some ways to perform global influence analysis. Finally, the methodology is illustrated on a medical data.     

曲线分类建模方法及其在GDP预测中的应用

传统方法解决大规模时序曲线的预测建模问题,需要对每条曲线逐一建模,使得建模工作量相当庞大,在实际应用中缺乏可操作性。文章提出一种解决此问题的新方法——曲线分类建模方法。该方法先减少曲线的模型种类,再进行曲线分类和分类建模,在尽可能保留原始信息的前提下较大程度地降低了建模的工作量。文章阐述了该方法的原理和计算过程,并以应用于多地区GDP曲线的预测案例说明该方法的实用性和有效性。     

Migration Decisions of Dual-earner Families: An Application of Multilevel Modeling

A comprehensive framework for guiding analyses of internal migration is lacking. This study contributes to the family migration literature in three important ways. We develop a multilevel theoretical framework emphasizing an integration of individual-, family-, and neighborhood-level effects; introduce multilevel statistical modeling; and explicitly assess how effects of economic-based explanatory variables vary by gender. Our data are from the Panel Study of Income Dynamics (PSID). We find that the likelihood of a family migrating is affected by economic and non-economic factors, some of which vary by gender. We add to the dual-earner migration literature by finding that wives are not likely to be tied-movers, but husbands are likely to be tied-stayers. Neighborhood factors also are important to the decision to migrate.

The Experience-Earnings Profile: Productivity-Augmenting or Purely Contractual? Evidence from the UK

We test the human capital interpretation of the experience-earnings profile. Does the upward sloping portion of the experience-earnings profile reflect on-the-job training which in turn causes the experience-productivity profile to slope upwards, or do purely contractual factors determine the nature of life-cycle earnings. Herein, we provide additional evidence on the relationship between productivity and earnings by examining earnings differentials in the UK academic labor market for economists. Using a test first suggested by Mincer, we find that the empirical results are consistent with human capital theory. We find that, although the positive relationship between earnings and experience persists when individual productivity measures are included in the salary equations for lecturers and senior lecturers, the positive relationship becomes statistically insignificant when the same productivity measures are included in the salary equations for professors. For lecturers and senior lecturers, the experience-salary profile properly reflects the structure of the national pay scale rather than variations in individual research productivity. At the professor level, where individual salaries are not determined by a pay scale, the data support the human capital explanation of the positive experience-earnings profile.

Construction Safety Risk Modeling and Simulation

By building on a genetic‐inspired attribute‐based conceptual framework for safety risk analysis, we propose a novel approach to define, model, and simulate univariate and bivariate construction safety risk at the situational level. Our fully data‐driven techniques provide construction practitioners and academicians with an easy and automated way of getting valuable empirical insights from attribute‐based data extracted from unstructured textual injury reports. By applying our methodology on a data set of 814 injury reports, we first show the frequency‐magnitude distribution of construction safety risk to be very similar to that of many natural phenomena such as precipitation or earthquakes. Motivated by this observation, and drawing on state‐of‐the‐art techniques in hydroclimatology and insurance, we then introduce univariate and bivariate nonparametric stochastic safety risk generators based on kernel density estimators and copulas. These generators enable the user to produce large numbers of synthetic safety risk values faithful to the original data, allowing safety‐related decision making under uncertainty to be grounded on extensive empirical evidence. One of the implications of our study is that like natural phenomena, construction safety may benefit from being studied quantitatively by leveraging empirical data rather than strictly being approached through a managerial perspective using subjective data, which is the current industry standard. Finally, a side but interesting finding is that in our data set, attributes related to high energy levels (e.g., machinery, hazardous substance) and to human error (e.g., improper security of tools) emerge as strong risk shapers.     

Effect of aggregation on the estimation of trend in mortality

There are three approaches to analyzing and forecasting age‐specific mortality: (1) analyze age‐specific data directly, (2) analyze each cause‐specific mortality series separately and add the results, (3) analyze cause‐specific mortality series jointly and add the results. We show that if linear models are used for cause‐specific mortality, then the three approaches often give close results even when cause‐specific series are correlated. This result holds for cross‐correlations arising from random misclassification of deaths by cause, and also for certain patterns of systematic misclassification. It need not hold, if one or more causes serve as “leading indicators”; for the remaining causes, or if outside information is incorporated into forecasting either through expert judgment or formal statistical modeling. Under highly nonlinear models or in the presence of modeling error the result may also fail. The results are illustrated with U.S. age‐specific mortality data from 1968–1985. In some cases the aggregate forecasts appear to be the more credible ones.     

Construction of Confidence Intervals for the IVIean of a Population Containing Many Zero Values

The likelihood ratio method is used to construct a confidence interval for a population mean when sampling from a population with certain characteristics found in many applications, such as auditing. Specifically, a sample taken from this type of population usually consists of a very large number of zero values, plus a small number of nonzero values that follow some continuous distribution. In this situation, the traditional confidence interval constructed for the population mean is known to be unreliable. This article derives confidence intervals based on the likelihood-ratio-test approach by assuming (1) a normal distribution (normal algorithm) and (2) an exponential distribution (exponential algorithm). Because the error population distribution is usually unknown, it is important to study the robustness of the proposed procedures. We perform an extensive simulation study to compare the percentage of confidence intervals containing the true population mean using the two proposed algorithms with the percentage obtained from the traditional method based on the central limit theorem. It is shown that the normal algorithm is the most robust procedure against many different distributional error assumptions.     

基于Solid works蜗轮蜗杆三维建模的研究

在Solid works环境下进行了蜗轮蜗杆三维设计研究,这对类似复杂曲面的零件设计具有实际意义。