Inferences on functions of Pareto parameters with application to income inequality measures

The Theil, Pietra, Éltetö and Frigyes measures of income inequality associated with the Pareto distribution function are expressed in terms of parameters defining the Pareto distribution. Inference procedures based on the generalized variable method, the large sample method, and the Bayesian method for testing of, and constructing confidence interval for, these measures are discussed. The results of Monte Carlo study are used to compare the performance of the suggested inference procedures from a population characterized by a Pareto distribution.     

联盟信任变迁与美韩联盟转型

联盟信任与联盟困境之间存在密切关系。在双边不对称联盟中,联盟困境的"抛弃"与"牵连"对联盟信任的作用更为强烈,进而成为推动联盟转型的重要变量。在美韩联盟发展过程中,其联盟信任不断变迁。联盟初期,由战火锤炼铸就的美韩双向情绪性信任,中经"尼克松冲击"转变为情绪性—工具性信任,后冷战时代历经双方的战略调整与实力变迁影响,转为双向工具性信任。受联盟信任变迁的影响,美韩联盟也实现了由军事联盟向战略性联盟的转变,这是联盟信任下降与共有利益拓展的共同结果。     

小学校长服务型领导对教师知识分享行为的影响研究

以山东省248名小学教师为有效样本，探讨了服务型领导、教师同事信任、情感承诺和教师知识分享行为之间的关系。研究结果显示：服务型领导与教师知识分享行为显著相关；教师同事信任部分居间联系了服务型领导与知识分享行为之间的关系；教师同事信任部分居间联系了服务型领导与情感承诺之间的关系；情感承诺对服务型领导与知识分享行为关系的中介作用不显著。     

Ridge Regression and Generalized Maximum Entropy: An improved version of the Ridge–GME parameter estimator

In this article, the Ridge–GME parameter estimator, which combines Ridge Regression and Generalized Maximum Entropy, is improved in order to eliminate the subjectivity in the analysis of the ridge trace. A serious concern with the visual inspection of the ridge trace to define the supports for the parameters in the Ridge–GME parameter estimator is the misinterpretation of some ridge traces, in particular where some of them are very close to the axes. A simulation study and two empirical applications are used to illustrate the performance of the improved estimator. A MATLAB code is provided as supplementary material.     

Changes in the Factors Influencing Public Acceptance of Nuclear Power Generation in Japan Since the 2011 Fukushima Daiichi Nuclear Disaster

Public support for nuclear power generation has decreased in Japan since the Fukushima Daiichi nuclear accident in March 2011. This study examines how the factors influencing public acceptance of nuclear power changed after this event. The influence factors examined are perceived benefit, perceived risk, trust in the managing bodies, and pro‐environmental orientation (i.e., new ecological paradigm). This study is based on cross‐sectional data collected from two online nationwide surveys: one conducted in November 2009, before the nuclear accident, and the other in October 2011, after the accident. This study's target respondents were residents of Aomori, Miyagi, and Fukushima prefectures in the Tohoku region of Japan, as these areas were the epicenters of the Great East Japan Earthquake and the locations of nuclear power stations. After the accident, trust in the managing bodies was found to have a stronger influence on perceived risk, and pro‐environmental orientation was found to have a stronger influence on trust in the managing bodies; however, perceived benefit had a weaker positive influence on public acceptance. We also discuss the theoretical and practical implications of these findings.     

The generalized odd half-Cauchy family of distributions: Properties and applications

We introduce and study general mathematical properties of a new generator of continuous distributions with one extra parameter called the generalized odd half-Cauchy family. We present some special models and investigate the asymptotics and shapes. The new density function can be expressed as a linear mixture of exponentiated densities based on the same baseline distribution. We derive a power series for the quantile function. We discuss the estimation of the model parameters by maximum likelihood and prove empirically the flexibility of the new family by means of two real data sets.     

基于思维法则学的跨文化信任框架——综合中国本土化思想与西方理论的尝试

以"承诺式信任"和"说服式信任"作为2个极端点,以"调节式信任"作为连续体的中间状态,提出了"信任的连续统一体"模型。该模型解释了中国情境下基于"关系"和"面子"的信任,以及西方基于认知、基于情感的信任;从调节式信任的角度,提出了跨文化信任的框架,分析了跨文化信任构建过程的一些阶段及调节策略;给出了关于发展中国管理理论、促进管理科学中国学派走向世界的思考。     

On Modeling Wood Formation Using Parametric and Semiparametric Regressions for Count Data

Understanding how wood develops has become an important problematic of plant sciences. However, studying wood formation requires the acquisition of count data difficult to interpret. Here, the annual wood formation dynamics of a conifer tree species were modeled using generalized linear and additive models (GLM and GAM); GAM for location, scale, and shape (GAMLSS); a discrete semiparametric kernel regression for count data. The performance of models is evaluated using bootstrap methods. GLM was useful to describe the wood formation general pattern but had a lack of fitting, while GAM, GAMLSS, and kernel regression had a higher sensibility to short-term variations.