基于局部社团结构平衡的双模符号网络链路预测研究

随着互联网产业的高速发展,双模符号网络已经成为一类常见的复杂网络,然而针对此 类网络的分析较少。本文在传统非符号网络局部社团理论和符号网络结构平衡理论的基础上,首次提出了双模符号网络下的局部社团理论。这一理论不仅考虑了符号网络中共同邻居的信息,还引入了共同邻居间存在的连接。进一步地,本文推导出符号网络中基于局部社团信息的加权平衡回路增益指数,该指标可以表示双模符号网络中用户节点和产品节点间的符号关系。为了将该指标更好地应用于双模 符号网络链路预测问题,本文提出了加权平衡回路增益分类器算法。实验结果表明,相比其他经典链路预测算法,新算法具有更好的预测能力。     

地方普通本科院校办学定位及分类发展研究--以广西为例

通过非介入性研究方法，对广西普通本科院校办学定位进行分析，从办学目标、办学类型、办学层次、人才培养、服务面向等六个方面论述办学定位现状，分析定位特征及其存在的问题。     

Assessment of modeling longitudinal binary data based on graphical methods

Longitudinal categorical data are commonly applied in a variety of fields and are frequently analyzed by generalized estimating equation (GEE) method. Prior to making further inference based on the GEE model, the assessment of model fit is crucial. Graphical techniques have long been in widespread use for assessing the model adequacy. We develop alternative graphical approaches utilizing plots of marginal model-checking condition and local mean deviance to assess the GEE model with logit link for longitudinal binary responses. The applications of the proposed procedures are illustrated through two longitudinal binary datasets.     

LAN property for an ergodic Ornstein–Uhlenbeck process with Poisson jumps

In this article, we consider an ergodic Ornstein–Uhlenbeck process with jumps driven by a Brownian motion and a compensated Poisson process, whose drift and diffusion coefficients as well as its jump intensity depend on unknown parameters. Considering the process discretely observed at high frequency, we derive the local asymptotic normality property. To obtain this result, Malliavin calculus and Girsanov’s theorem are applied to write the log-likelihood ratio in terms of sums of conditional expectations, for which a central limit theorem for triangular arrays can be applied.     

A robust and efficient estimation method for nonparametric models with jump points

Nonparametric models with jump points have been considered by many researchers. However, most existing methods based on least squares or likelihood are sensitive when there are outliers or the error distribution is heavy tailed. In this article, a local piecewise-modal method is proposed to estimate the regression function with jump points in nonparametric models, and a piecewise-modal EM algorithm is introduced to estimate the proposed estimator. Under some regular conditions, the large-sample theory is established for the proposed estimators. Several simulations are presented to evaluate the performances of the proposed method, which shows that the proposed estimator is more efficient than the local piecewise-polynomial regression estimator in the presence of outliers or heavy tail error distribution. What is more, the proposed procedure is asymptotically equivalent to the local piecewise-polynomial regression estimator under the assumption that the error distribution is a Gaussian distribution. The proposed method is further illustrated via the sea-level pressures.     

A class of partially linear transformation models for recurrent gap times

In this article, we propose a general class of partially linear transformation models for recurrent gap time data, which extends the linear transformation models by incorporating non linear covariate effects and includes the partially linear proportional hazards and the partially linear proportional odds models as special cases. Both global and local estimating equations are developed to estimate the parametric and non parametric covariate effects, and the asymptotic properties of the resulting estimators are established. The finite-sample behavior of the proposed estimators is evaluated through simulation studies, and an application to a clinic study on chronic granulomatous disease is provided.     

Promoting sustainable development through civil society: A case study of the EU’s NSA/LA thematic programme in Kyrgyzstan

The article focuses on the contribution of the European Union (EU) in promoting sustainable development through the involvement of civil society in partner countries. More specifically, it analyses the main features and outcomes of the projects implemented by civil society organizations (CSOs) in Kyrgyzstan under the EU thematic programme Non‐State Actors and Local Authorities in Development (NSA/LA). Despite its importance—this is the only EU programme providing direct support to non‐state actors and local authorities engaged in poverty reduction—to date, there has been very little research on the functioning of this instrument on the ground. This article seeks to fill this gap in the literature by examining the EU’s contribution to sustainable development through a case study on Kyrgyzstan. The study is based on primary data: 10 semi‐structured interviews conducted with the EU‐funded organizations implementing the NSA/LA programme. The NSA/LA projects were analysed by considering two major fields of engagement of non‐state actors in the development process: as service providers and as advocates (Banks & Hulme, 2012). Overall, the organizations awarded EU support were not only focused on fulfilling short‐term needs but also sought to introduce new ways of dealing with poverty and inequality, positioning themselves between the “Big‐D” and the “little‐d” approaches to development (Bebbington, Hickey, & Mitlin, 2008). Nonetheless, the EU‐funded projects were too limited and fragmented to be able to sustain long‐term structural change. Therefore, the EU should place new emphasis on creating synergies between new and old structures at the grassroots level and establishing mechanisms and bodies that could merge and co‐ordinate their efforts. In addition, the calls for proposals could highlight the need to share the lessons learnt by “obliging” the beneficiaries to act as multipliers and to pass on their positive experience to neighbouring communities. Finally, the EU could stimulate the funded organizations to experiment with innovative mechanisms of involvement in the policy‐making process, by making this aspect a mandatory requirement of the projects implemented with its support.     

Dimension reduction via local rank regression

Outer product of gradients (OPG) achieves dimension reduction via estimating the gradients of the regression function. In this paper, we propose two novel OPG estimators via local rank regression: the rank OPG estimator and the Walsh-average OPG estimator. Both proposals guard against a wide range of error distributions, and are safe alternatives to existing OPG estimators based on local linear regression or local L1 regression. The effectiveness of the new proposals are demonstrated via extensive numerical studies.     

Graphical and Numerical Methods for Detecting Influential Observations in Complex Bingham Data

We describe methods to detect influential observations in a sample of pre-shapes when the underlying distribution is assumed to be complex Bingham. One of these methods is based on Cook's distance, which is derived from the likelihood of the complex Bingham distribution. Other method is related to the tangent space, which is based on the local influence for the multivariate normal distribution. A method to detect outliers is also explained. The application of the methods is illustrated in both a real dataset and a simulated sample.     

局部均衡函数及其构造

研究了局部均衡函数,定义了改进的局部变权向量,提出了与之对应的状态局部变权向量和局部均衡函数,证明了两类函数是局部均衡函数;利用局部变权向量建立了企业信用评估模型,并通过实例说明了该理论是有效的和合理的.