Culture‐Inclusive Theories of Self and Social Interaction: The Approach of Multiple Philosophical Paradigms

In view of the fact that culture‐inclusive psychology has been eluded or relatively ignored by mainstream psychology, the movement of indigenous psychology is destined to develop a new model of man that incorporates both causal psychology and intentional psychology as suggested by Vygotsky (1927). Following the principle of cultural psychology: “one mind, many mentalities” (Shweder et al., 1998), the Mandala Model of Self (Hwang, 2011a,b) and Face and Favor Model (Hwang, 1987, 2012) were constructed to represent the universal mechanisms of self and social interaction that can be applied to any culture; both models can be used as conceptual frameworks for analyzing mentalities of people in any given culture. Taking research works from Foundations of Chinese Psychology: Confucian Social Relation as exemplars (Hwang, 2012), this article illustrates how to construct culture‐inclusive theories of Confucianism by multiple philosophical paradigms. The mechanism of culture‐inclusive theory can be applied to explain qualitative research findings on lifeworld events of people in a particular society. It can also be utilized to predict results of quantitative research conducted to verify theoretical propositions in the scientific microworld by empirical methods.     

Methods to Distinguish Between Polynomial and Exponential Tails

Two methods to distinguish between polynomial and exponential tails are introduced. The methods are based on the properties of the residual coefficient of variation for the exponential and non‐exponential distributions. A graphical method, called a CV‐plot, shows departures from exponentiality in the tails. The plot is applied to the daily log‐returns of exchange rates of US dollar and Japanese yen. New statistics are introduced for testing the exponentiality of tails using multiple thresholds. They give better control of the significance level than previous tests. The powers of the new tests are compared with those of some others for various sample sizes.     

Detection of multiple undocumented change-points using adaptive Lasso

The problem of detecting multiple undocumented change-points in a historical temperature sequence with simple linear trend is formulated by a linear model. We apply adaptive least absolute shrinkage and selection operator (Lasso) to estimate the number and locations of change-points. Model selection criteria are used to choose the Lasso smoothing parameter. As adaptive Lasso may overestimate the number of change-points, we perform post-selection on change-points detected by adaptive Lasso using multivariate t simultaneous confidence intervals. Our method is demonstrated on the annual temperature data (year: 1902–2000) from Tuscaloosa, Alabama.     

制造商供应量变化时同质多物品拍卖价格策略研究

本文分析了制造商供应量变化时、在多个零售商非单位需求情形下的统一价格拍卖与歧视价格拍卖,得到了两种拍卖方式下零售商的报价策略、制造商的价格策略及其相关性质。结果表明:统一价格拍卖中,零售商在低价时所提交数量高于其真实需求,在高价时所提交数量低于其真实需求。歧视价格拍卖中零售商在低价会选择提交自己真实的需求量,在高价会选择提交低于真实的需求量。若参与拍卖的零售商越多,相对歧视价格拍卖,统一价格拍卖提交的需求量扭曲越少,从机制设计的角度来看,制造商更倾向于用统一价格拍卖的方式进行产品批发。       

Verification bias on sensitivity and specificity measurements in diagnostic medicine: a comparison of some approaches used for correction

Verification bias may occur when the test results of not all subjects are verified by using a gold standard. The correction for this bias can be made using different approaches depending on whether missing gold standard test results are random or not. Some of these approaches with binary test and gold standard results include the correction method by Begg and Greenes, lower and upper limits for diagnostic measurements by Zhou, logistic regression method, multiple imputation method, and neural networks. In this study, all these approaches are compared by employing a real and simulated data under different conditions.     

重尾索赔条件下现代风险模型的破产概率估计:多险种混合情形

破产概率是非寿险保险风险理论的核心问题。与经典的Cramér-Lundberg模型相比, 由Li Zehui等建立的现代风险模型更为准确地描述了非寿险保险运营的主要特征, 对现实保险业务具有较好的解释力。本文基于现代风险模型, 考虑保险公司多个险种混合经营这一更为现实的情形, 在索赔额服从正则尾分布条件下获得了破产概率的渐近等价估计。我们发现, 在具有大额索赔特征的多个险种混合的条件下, 公司面临的极端索赔风险将由索赔额分布尾部最厚的那些险种决定, 而索赔额分布尾部相对较薄的那些险种的影响作用将被淹没。该结论的有效性可用MATLAB数值模拟得到理想的验证。本文结果是对风险模型研究的重要推广, 也为多险种混合情形下保险公司的风险控制与初始保证金界定提供了依据。     

上海多性伴性行为现状及其影响因素研究

本文利用上海市的调查数据,首先考察了上海市多性伴性行为的性别差异,接着从阶层归属、家庭亲属生活、性爱生活和性别规范四个层面对多性伴性行为的影响因素进行理论建构。研究结果表明：在多性伴性行为中,“生理需要论”并不起作用;“资本运作”和“环境影响”取代“阶层归属”发挥显性作用;“婚内感情论”具有一定合理性但也存在时效性,“头两年之痒”和“七年之痒”并存;“越轨”性行为具有连贯性;性别规范通过中间变量（两性在社会、家庭和性领域的角色扮演）间接影响两性的性活动方式。因此,我们需要以社会性别视角鉴别女性“性革命”成功与否,思考女性在性地位上是真正解放还是重新被奴役。     

Variable selection models based on multiple imputation with an application for predicting median effective dose and maximum effect

The statistical methods for variable selection and prediction could be challenging when missing covariates exist. Although multiple imputation (MI) is a universally accepted technique for solving missing data problem, how to combine the MI results for variable selection is not quite clear, because different imputations may result in different selections. The widely applied variable selection methods include the sparse partial least-squares (SPLS) method and the penalized least-squares method, e.g. the elastic net (ENet) method. In this paper, we propose an MI-based weighted elastic net (MI-WENet) method that is based on stacked MI data and a weighting scheme for each observation in the stacked data set. In the MI-WENet method, MI accounts for sampling and imputation uncertainty for missing values, and the weight accounts for the observed information. Extensive numerical simulations are carried out to compare the proposed MI-WENet method with the other competing alternatives, such as the SPLS and ENet. In addition, we applied the MI-WENet method to examine the predictor variables for the endothelial function that can be characterized by median effective dose (ED50) and maximum effect (Emax) in an ex-vivo phenylephrine-induced extension and acetylcholine-induced relaxation experiment.     

Power and stability comparisons of multiple testing procedures with false discovery rate control

High-throughput data analyses are widely used for examining differential gene expression, identifying single nucleotide polymorphisms, and detecting methylation loci. False discovery rate (FDR) has been considered a proper type I error rate to control for discovery-based high-throughput data analysis. Various multiple testing procedures have been proposed to control the FDR. The power and stability properties of some commonly used multiple testing procedures have not been extensively investigated yet, however. Simulation studies were conducted to compare power and stability properties of five widely used multiple testing procedures at different proportions of true discoveries for various sample sizes for both independent and dependent test statistics. Storey's two linear step-up procedures showed the best performance among all tested procedures considering FDR control, power, and variance of true discoveries. Leukaemia and ovarian cancer microarray studies were used to illustrate the power and stability characteristics of these five multiple testing procedures with FDR control.     

Assessment of supplier performance based on product-development strategy by applying multi-granularity linguistic term sets

Measuring supplier performance possesses the properties of multi-dimension and multi-scale, it increases the complexity of the aggregation and assessment process. A focal company must develop an effective procedure for overcoming the complexity of performance measurement. Furthermore, the assessment of supplier performance must conform to the product-developed strategy of the focal company. This study is a further research deeper into the concept already introduced in Chang et al. [1] [Applying fuzzy linguistic quantifier to select supply chain partners at different phases of product life cycle. International Journal of Production Economics 2006; 100(2):348–59]; using multi-granularity linguistic variable and numerical ration scale to represent the overall supply performance. By unifying the derived information, the measurement complexity could be resolved. The fuzzy preference was constructed to adjust the consistent direction and transform information into fuzzy relationship. Finally, fuzzy linguistic quantifier guided ordered weighted aggregation (FLQG-OWA) operator with maximal entropy was computed and aggregated with all indicators to meet the current policy of the focal company.