Quasi-minimax estimation in the partial linear model

This article discusses the minimax estimator in partial linear model y = Zβ + f + ε under ellipsoidal restrictions on the parameter space and quadratic loss function. The superiority of the minimax estimator over the two-step estimator is studied in the mean squared error matrix criterion.     

Numerical evaluation of tests based on different heteroskedasticity-consistent covariance matrix estimators

This article considers the issue of performing tests in linear heteroskedastic models when the test statistic employs a consistent variance estimator. Several different estimators are considered, namely: HC0, HC1, HC2, HC3, and their bias-adjusted versions. The numerical evaluation is performed using numerical integration methods; the Imhof algorithm is used to that end. The results show that bias-adjustment of variance estimators used to construct test statistics delivers more reliable tests when they are performed for the HC0 and HC1 estimators, but the same does not hold for the HC3 estimator. Overall, the most reliable test is the HC3-based one.     

Curation: a theoretical treatment

Curation is a key mechanism of sociality in a digital era. With an abundance of information, sifting, sorting, selecting, hiding, and standing out become laborious tasks. While researchers have diligently documented people’s curatorial strategies, digital curation remains undertheorized in its own right. I therefore theorize digital curation by disentangling productive curation from consumptive curation, addressing how people curate content that they share, and that which they consume. I embed these agentic curatorial practices within structural bounds, both social and technological. In doing so, I offer a basic theoretical model that captures a dynamic relationship between individual curators, their social networks, and technological design.     

数字化生存的道德风险与信息崇拜的伦理考辨

当代人尤其是青年人面临诸多现实世界中自我难以解决的矛盾和困惑时,期许能在电子＂伊甸园＂中找回自我价值和精神皈依。然而,虚拟空间并非想象中的天堂,类似＂面具＂的交流形式遮蔽着许多本真的存在,消解了现实世界的核心价值;游离在虚拟和现实之间的自我与社会脱离;对网络的过渡依赖性导致人格的异化;方向感的迷茫和自我定位的偏差,使得价值追求从崇高滑向流俗甚至恶俗。数字化生存方式正颠覆着传统生活方式和现实生活世界的诸多价值标准,而信息崇拜的推波助澜,更使人们产生了一种莫名的幸福被剥夺的感觉。     

Symmetrical design for symmetrical global sensitivity analysis of model output

Symmetrical global sensitivity analysis (SGSA) can help practitioners focusing on the symmetrical terms of inputs whose uncertainties have an impact on the model output, which allows reducing the complexity of the model. However, there remains the challenging problem of finding an efficient method to get symmetrical global sensitivity indices (SGSI) when the functional form of the symmetrical terms is unknown, including numerical and non-parametric situations. In this study, we propose a novel sampling plan, called symmetrical design, for SGSA. As a preliminary experiment for model feature extracting, such plan offers the virtue of run-size economy due to its closure respective to the given group. Using the design, we give estimation methods of SGSI as well as their asymptotic properties respectively for numerical model and non-parametrical model directly by the model outputs, and further propose a significance test for SGSI in non-parametric situation. A case study for a benchmark of GSA and a real data analysis show the effectiveness of the proposed design.     

新媒介背景的儿童类纸质媒体发展取向

数字媒介技术的革新加剧了“图像革命”，造成了人的思考能力的滑坡．这一影响加之于儿童则更加明显。儿童作为特殊且脆弱的社会群体，极易陷入新媒介所搅动的文化漩涡中，传统阅读这一儿童基础性认知技能遭遇到严峻考验。儿童类纸质媒体应充分发挥独有优势，与儿童类数字媒体展开错位竞争。从儿童文化内容的创作生产、儿童文化产品的销售渠道、儿童文化消费的最终实现三个层面完成自身的发展与跨越。     

A New Feature Selection Method for Text Categorization of Customer Reviews

With the rapid development of e-commerce, online consumer review plays an increasingly important role in consumers’ purchase decisions. Most research papers use the quantitative measures of consumer reviews for statistical analysis. Here we focus on analyzing the texts of customer reviews with text mining tools. We propose a new feature selection method called maximizing the difference. Various classification methods such as boosting, random forest and SVM are used to test the performance of the new method along with different evaluation criteria. Both simulation and empirical results show that it improves the effectiveness of the classifier over the existing methods.     

Modified linear discriminant analysis using block covariance matrix in high-dimensional data

Among many classification methods, linear discriminant analysis (LDA) is a favored tool due to its simplicity, robustness, and predictive accuracy but when the number of genes is larger than the number of observations, it cannot be applied directly because the within-class covariance matrix is singular. Also, diagonal LDA (DLDA) is a simpler model compared to LDA and has better performance in some cases. However, in reality, DLDA requires a strong assumption based on mutual independence. In this article, we propose the modified LDA (MLDA). MLDA is based on independence, but uses the information that has an effect on classification performance with the dependence structure. We suggest two approaches. One is the case of using gene rank. The other involves no use of gene rank. We found that MLDA has better performance than LDA, DLDA, or K-nearest neighborhood and is comparable with support vector machines in real data analysis and the simulation study.     

社会化网络3维用户界面设计分析与研究

为了寻找三维用户界面设计策略，在归纳2维（2D）与2．5维（2．5D）用户界面包含的内容与设计策略的基础上，从3维（3D）用户界面的交互任务、信息呈现和用户搜索行为三方面进行了分析，整合了用户需求、空间行为、空间任务，创新性地构建了面向真3D空间的“需求-任务-层次模型”，为3D用户界面的构建提供了新的思路。此外，从细节层面对3D用户界面具体设计原则进行分析，提出了“信息呈现设计矩阵”，对3D用户界面设计具有一定的指导意义。     

On the construction of optimal experimental designs: a penalty approach

Tn optimal experimental design theory there are well-known situations, in which additional constraints are implied to the design set. These constraints destroy in general the simplex structure of the set of feasible points of the design set. Thus the available iteration procedures for the unrestricted case are no longer applicable.

In this paper a penalty approach is suggested which transforms the restricted problem to the unrestricted case and allows the application of well-known algorithms such as the Fedorov-Wynn-type or the projected gradient procedure.