L2句子加工心理机制的ERPs研究及问题思考

国内外对L2句子加工的研究存在着较大区别。国外偏重于探讨句子加工的心理机制本身,而国内不仅探讨句子加工的心理机制本身,而且还注重探讨句子加工的心理机制所说明的问题,分析L2句子加工是否接近或相似于L1句子加工。目前,该领域的研究主要存在三种主要流派:模块说、交互说和平行说。多数学者认为L2句子加工是句法和语义加工交织的过程,即多数人接受了交互说。少数学者认为语义加工优先于句法加工。至于平行说,最近L2句子加工研究鲜有成果支持此理论。     

P2P技术与网络传播的未来

伴随着P2P技术和商业应用的发展,P2P技术对于未来网络传播可能产生的影响也成为一个令 人关注的问题。从目前来看,P2P技术对于网络传播的影响主要包括以下几方面:网络信息共享与 利用的方式与程度将进一步改变;围绕P2P技术思想展开的软件与信息产品开发,将在一定程度上 决定作为媒体的网络的未来面貌;P2P带来的去中心化特点将使互联网管理的难度进一步增加; P2P可能成为媒体间的交流与合作的新平台,也可能加速媒体形态的演化。从总体看,P2P技术未 来的社会影响程度,取决于政治、经济等各种力量的博弈结果,而这也将最终影响着互联网的未来。     

Gender differences in risk behavior and the link to household effects and individual wealth

This study examined the differences in risk behavior between men and women using a household survey that captured the risk preferences of two members in a household and recorded wealth at the individual level instead of the usual approach of representing wealth at the household level. After controlling for commonly used explanatory variables, such as gender, education, age, and wealth, household fixed effects explain about 15% of the variation in risk behavior. This highlights the magnitude of household effects in shaping one’s risk behavior. In general, females in the study area are more risk averse than males based on a risk game with real payout. The gender differences disappear when focusing on only the top land owners. However, even in those cases, females consider themselves more risk averse, supporting results from previous studies that link culture and societal norms to the gender differences in risk behavior.     

Variance estimation based on blocked 3×2 cross-validation in high-dimensional linear regression

In high-dimensional linear regression, the dimension of variables is always greater than the sample size. In this situation, the traditional variance estimation technique based on ordinary least squares constantly exhibits a high bias even under sparsity assumption. One of the major reasons is the high spurious correlation between unobserved realized noise and several predictors. To alleviate this problem, a refitted cross-validation (RCV) method has been proposed in the literature. However, for a complicated model, the RCV exhibits a lower probability that the selected model includes the true model in case of finite samples. This phenomenon may easily result in a large bias of variance estimation. Thus, a model selection method based on the ranks of the frequency of occurrences in six votes from a blocked 3×2 cross-validation is proposed in this study. The proposed method has a considerably larger probability of including the true model in practice than the RCV method. The variance estimation obtained using the model selected by the proposed method also shows a lower bias and a smaller variance. Furthermore, theoretical analysis proves the asymptotic normality property of the proposed variance estimation.     

P2P 网络借贷研究进展及中国问题研究展望

P2P ( 个人对个人) 网络借贷是指通过网络借贷平台,在全球范围内实现个人与个人或小微企业间的小额信用借贷交易． P2P 网络借贷作为全新的互联网金融服务受到商业界的高度关注,而且发展成为学术研究的国际前沿领域． 对 P2P 网络借贷相关研究文献进行了综述,具体从影响借贷交易的信息因素、羊群效应以及社交网络等 3 个方面分析了该领域研究的现状和发展脉络． 因为中国已超越美国成为全球最大的 P2P 网络借贷交易市场,所以结合中国的具体情境和问题,提出了未来研究工作的展望．     

中国P2P网络借贷信用风险的测量

分析中国P2P网络借贷信用风险的生成机理,借鉴商业银行典型个人信用风险测量理论基础与方法,构建基于涵盖借款人软信息的P2P网络借贷信用风险评级指标体系。通过向在银行从事信贷工作的专业人员发放调查问卷,确定具体指标,使用AHP(层次分析法)与DEMATEL(决策实验室法)相结合的方法综合确定指标体系权重,最后评级结果以百分制数值给出,并换算成具体的信用等级,有效解决了平台对借款人信用等级测量问题。     

A powerful and efficient algorithm for breaking the links between aliased effects in asymmetric designs

Fractional factorial (FF) designs are no doubt the most widely used designs in experimental investigations due to their efficient use of experimental runs. One price we pay for using FF designs is, clearly, our inability to obtain estimates of some important effects (main effects or second order interactions) that are separate from estimates of other effects (usually higher order interactions). When the estimate of an effect also includes the influence of one or more other effects the effects are said to be aliased. Folding over an FF design is a method for breaking the links between aliased effects in a design. The question is, how do we define the foldover structure for asymmetric FF designs, whether regular or nonregular? How do we choose the optimal foldover plan? How do we use optimal foldover plans to construct combined designs which have better capability of estimating lower order effects? The main objective of the present paper is to provide answers to these questions. Using the new results in this paper as benchmarks, we can implement a powerful and efficient algorithm for finding optimal foldover plans which can be used to break links between aliased effects.     

Personality profiles of factitious disorder imposed by mothers: A comparative analysis

Factitious Disorder Imposed by Another (FDIA) can be difficult to expeditiously identify. Understanding personality characteristics of FDIA perpetrators via psychological assessment may decrease the time between initial abuse and identification of FDIA. Personality characteristics of FDIA mother-perpetrators were examined through a comparative analysis of MMPI-2 profiles. It was predicted that mother-perpetrators would have significantly higher overall profile elevations on the MMPI-2 and elevations on specific clinical scales than a comparative control group. Results indicated that mother-perpetrators displayed significantly higher, elevations on the Psychasthenia (Pt) and Schizophrenia (Sc) scales and a trend toward significantly higher elevation on the Psychopathic Deviate (Pd) scale than the control group. These findings, along with the demographic information obtained, establish a preliminary foundation for understanding an overall profile of mother-perpetrators.     

Bootstrap methods for multivariate hypothesis testing

The nonparametric and parametric bootstrap methods for multivariate hypothesis testing are developed. They are used to approximate the null distribution of the test statistics proposed by Duchesne and Francq (2015 Duchesne, P., Francq, C. (2015). Multivariate hypothesis testing using generalized and {2}-inverses—with applications. Statistics 49:475–496.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]), resulting in bootstrap testing procedures. In the problem of testing for the mean vector of a multivariate distribution, the asymptotic validity of the bootstrap methods is proved. The finite sample performance of the new solutions is demonstrated by means of Monte Carlo simulation studies. They indicate that for small-sample size, the bootstrap tests provide a better finite sample properties than the asymptotic tests considered by Duchesne and Francq (2015 Duchesne, P., Francq, C. (2015). Multivariate hypothesis testing using generalized and {2}-inverses—with applications. Statistics 49:475–496.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]).