论社区共同体生成的政府培育主导路径

本文通过对朝阳区的实证研究,表明我国现阶段社区共同体的生成路径是政府培育主导。它的出现是历史发展的必然结果:在建国初期的单位共同体下,人们不仅缺乏结社传统,而且形成了对政府的依赖心理,致使我国社区共同体生成的主导方式一直是政府生成路径。但在现阶段,政府生成路径已经发生转变,变成了政府培育主导,而不是单位共同体下的政府控制主导,这体现了社区建设的发展方向是社区自治而不是社区控制。     

Testing the Significance of Categorical Predictor Variables in Nonparametric Regression Models

In this paper we propose a test for the significance of categorical predictors in nonparametric regression models. The test is fully data-driven and employs cross-validated smoothing parameter selection while the null distribution of the test is obtained via bootstrapping. The proposed approach allows applied researchers to test hypotheses concerning categorical variables in a fully nonparametric and robust framework, thereby deflecting potential criticism that a particular finding is driven by an arbitrary parametric specification. Simulations reveal that the test performs well, having significantly better power than a conventional frequency-based nonparametric test. The test is applied to determine whether OECD and non-OECD countries follow the same growth rate model or not. Our test suggests that OECD and non-OECD countries follow different growth rate models, while the tests based on a popular parametric specification and the conventional frequency-based nonparametric estimation method fail to detect any significant difference.     

用氢作涡流室柴油机副燃料的可能性研究

用 S195柴油机为试验样机,采取在进气过程中吸入少量氢气的方法,通过台架试验及分析,探讨了用氢作为涡流室柴油机副燃料的可能性及其实用价值。结果表明,吸入副燃料氢能显著改善燃烧,提高发动机性能,但保证性能良好的许用吸氢量具有一定限度,并存在最佳值;用氢作副燃料时,仅需适当增大涡流室通道截面比,而无需变动燃烧系统其它参数,即可获得较好效果。     

移动支付使用者使用意向与使用行为模型及实证研究

为了了解影响移动支付使用者使用意向与实际使用的因素,对基于整合型信息接受模型的新增成本影响因素进行验证性因子分析.结果显示:移动支付使用成本对移动支付使用意愿有着最显著的影响,社会影响、努力期望和期望效用对移动支付使用意愿具有显著的正向影响;移动支付使用意愿和便利条件对使用行为有着非常显著的积极影响.     

大股东控制影响公司现金持有量的实证分析

 本文结合我国上市公司所面临的内部治理机制特点及外部治理环境,从大股东行为的视角对公司现金持有量的影响因素进行实证分析。在加入年度控制变量、行业控制变量和公司财务特征控制变量后,对三项反映大股东行为特征的因素,即大股东持股比例、大股东属性和制度环境因素对公司现金持有量的影响进行了检验。结果表明,第一大股东持股比例较高的公司持有较多的现金,大股东的高持股比例是其占用企业资金侵占中小股东利益的基础。与国有企业相比,民营企业因遭受较强的外部融资约束而持有较高水平的现金。此外,制度环境的发展程度与公司现金持有水平正相关,表明制度环境较好地区的公司持有较多的现金。     

A tutorial on rank-based coefficient estimation for censored data in small- and large-scale problems

The analysis of survival endpoints subject to right-censoring is an important research area in statistics, particularly among econometricians and biostatisticians. The two most popular semiparametric models are the proportional hazards model and the accelerated failure time (AFT) model. Rank-based estimation in the AFT model is computationally challenging due to optimization of a non-smooth loss function. Previous work has shown that rank-based estimators may be written as solutions to linear programming (LP) problems. However, the size of the LP problem is O(n ²+p) subject to n ² linear constraints, where n denotes sample size and p denotes the dimension of parameters. As n and/or p increases, the feasibility of such solution in practice becomes questionable. Among data mining and statistical learning enthusiasts, there is interest in extending ordinary regression coefficient estimators for low-dimensions into high-dimensional data mining tools through regularization. Applying this recipe to rank-based coefficient estimators leads to formidable optimization problems which may be avoided through smooth approximations to non-smooth functions. We review smooth approximations and quasi-Newton methods for rank-based estimation in AFT models. The computational cost of our method is substantially smaller than the corresponding LP problem and can be applied to small- or large-scale problems similarly. The algorithm described here allows one to couple rank-based estimation for censored data with virtually any regularization and is exemplified through four case studies.     

A likelihood ratio test for goodness‐of‐fit of recessive and dominant models for case–control studies

Testing goodness‐of‐fit of commonly used genetic models is of critical importance in many applications including association studies and testing for departure from Hardy–Weinberg equilibrium. Case–control design has become widely used in population genetics and genetic epidemiology, thus it is of interest to develop powerful goodness‐of‐fit tests for genetic models using case–control data. This paper develops a likelihood ratio test (LRT) for testing recessive and dominant models for case–control studies. The LRT statistic has a closed‐form formula with a simple $\chi^{2}(1)$ null asymptotic distribution, thus its implementation is easy even for genome‐wide association studies. Moreover, it has the same power and optimality as when the disease prevalence is known in the population. The Canadian Journal of Statistics 41: 341–352; 2013 © 2013 Statistical Society of Canada     

Correlation Coefficient Revisited

Elementary approaches to prove basic properties of the correlation coefficient are of pedagogical interest. Besides posing another proof, this article gives variations of the proofs already existing in the statistical literature