Modeling probability density through ultraspherical polynomial transformations

We present a method for fitting parametric probability density models using an integrated square error criterion on a continuum of weighted Lebesgue spaces formed by ultraspherical polynomials. This approach is inherently suitable for creating mixture model representations of complex distributions and allows fully autonomous cluster analysis of high-dimensional datasets. The method is also suitable for extremely large sets, allowing post facto model selection and analysis even in the absence of the original data. Furthermore, the fitting procedure only requires the parametric model to be pointwise evaluable, making it trivial to fit user-defined models through a generic algorithm.     

反腐倡廉效率评估:方法选择与指标构建

对反腐倡廉建设开展效率评估,不仅有利于改进和提升反腐倡廉的效率,推进反腐倡廉建设科学化的进程,还能为反腐倡廉形势评估开辟一个独特的视角。文章在综述国内反腐倡廉建设评估研究的基础上,提出了反腐倡廉效率评估的必要性;并基于反腐倡廉建设目标与特点分析,论证了数据包络分析方法对反腐倡廉效率评估的适用性;参照学术界已有的成果,结合实践逻辑构建了反腐倡廉效率评估指标体系;阐述了数据包络分析的模型选择及运算过程。     

On the enumeration of rectangular (0, 1)-matrices

The construction and enumeration of (0, 1)-matrices with given line-sums is described for the rectangular cases often encountered in applications. Improved approximations are provided for the number of such matrices. Some new enumeration results for semi-regular bipartite graphs are included, and the related category of the quasi-semiregular bipartite graphs is recognized. The range of certain elements of products of a (0, I)-matrix is considered as a function of the line-sums. This, in turn, is related to the range in the numbers of interchanges available. Improvements in statistical practice that come from these constructions and enumerations are described.     

On the reciprocity of connections in weighted and unweighted networks

Bivariate Bernoulli and bivariate geometric distributions are proposed to model reciprocity in weighted and unweighted networks. Sampling properties of commonly used reciprocity measures are studied, under both presence and absence of reciprocity. Extensions to situations where link parameters depend on outgoing and incoming nodes are investigated. Results are illustrated with a data set, on 50 anesthesia providers at a hospital, that describes the number of times an anesthesia provider starting an operation transfers his/her responsibilities to another anesthesia provider.     

Use of multiple cluster analysis methods to explore the validity of a community outcomes concept map

Concept mapping is now a commonly-used technique for articulating and evaluating programmatic outcomes. However, research regarding validity of knowledge and outcomes produced with concept mapping is sparse. The current study describes quantitative validity analyses using a concept mapping dataset. We sought to increase the validity of concept mapping evaluation results by running multiple cluster analysis methods and then using several metrics to choose from among solutions. We present four different clustering methods based on analyses using the R statistical software package: partitioning around medoids (PAM), fuzzy analysis (FANNY), agglomerative nesting (AGNES) and divisive analysis (DIANA). We then used the Dunn and Davies-Bouldin indices to assist in choosing a valid cluster solution for a concept mapping outcomes evaluation. We conclude that the validity of the outcomes map is high, based on the analyses described. Finally, we discuss areas for further concept mapping methods research.     

党政机构微博在突发事件中传播效果的影响因素及策略

在分析铁路货运量预测方法的基础上，针对标准BP神经网络的不足，提出改进的BP神经网络预测模型。首先,利用动态陡度因子来改变激励函数的陡峭程度，以此来得到更好的激励函数响应特征以及更好的非线性表达能力；其次，利用附加动量因子，通过对以前经验的积累，既降低了神经网络对误差曲面的局部细节敏感特性，又较好的遏制了神经网络易于限于局部最小的缺陷；最后，采取改变学习率的方法，给定一个较大的学习率初始值，在学习的过程中学习率不断减小，网络最终趋于稳定。改进BP算法既可以得到更优的解，还能够缩短训练时间。利用全国铁路货运     

Social network and family business: Uncovering hybrid family firms

What does it mean for a private enterprise in China to be embedded in a family? Our purpose here is twofold: (1) use social network analysis to describe what it means for a firm to be embedded in a family, (2) reveal from the application a new kind of firm, not family, yet akin to family. Armed with data on a large probability sample of private enterprises — a third of which meet ownership and employment criteria of being family businesses — we uncover a category of “hybrid family firms” that look modern in the style of firms that exclude family, but operate socially in ways similar to family firms. Our conclusion from summary statistics on the sample is that there are no differences in average performance level or network advantage for the three categories of businesses: family firms, hybrid family firms, and family-excluded firms. The fact that CEOs of family firms and hybrid family firms more often turn to family as key business contacts is a fact about network composition that raises no question about network mechanisms. Whether the CEO turns to more or fewer family contacts, government help is more likely with stronger political connections, and business success and survival are more likely with a large, open network. That said, the look-modern, act-traditional hybrid family firms stand alone in prospering with a CEO embedded in a closed business network. Recognition of hybrid family firms adds to the literature’s illustrations of social network analysis used to distinguish types of businesses and business people, and extends the population of organizations within which governance and strategy are likely to be better understood when viewed through a family logic.     

Hierarchical likelihood approach to non-Gaussian factor analysis

Factor models, structural equation models (SEMs) and random-effect models share the common feature that they assume latent or unobserved random variables. Factor models and SEMs allow well developed procedures for a rich class of covariance models with many parameters, while random-effect models allow well developed procedures for non-normal models including heavy-tailed distributions for responses and random effects. In this paper, we show how these two developments can be combined to result in an extremely rich class of models, which can be beneficial to both areas. A new fitting procedures for binary factor models and a robust estimation approach for continuous factor models are proposed.     

Queering Counselor Education: Situational Analysis of LGBTQ+ Competent Faculty

Research demonstrates counselor educators often lack skills and knowledge to train counselors to become lesbian, gay, bisexual, transgender, queer and other sexualities and gender identities (LGBTQ+) competent. This study explores the process of educators integrating LGBTQ+ competencies into their professional work. Using grounded theory and situational analysis methodologies, in-depth interviews with seven LGBTQ+ competent counselor educators were conducted and analyzed. Findings suggest educators infuse personal passion for LGBTQ+ topics into their professional work, experienced discrimination and resistance across multiple domains, infuse advocacy into their work, and have a similar definition of LGBTQ+ competent counseling. Various techniques are presented to help educators infuse LGBTQ+ competency in the classroom.