Quadratic Approximation via the SCAD Penalty with a Diverging Number of Parameters

The high-dimensional data arises in diverse fields of sciences, engineering and humanities. Variable selection plays an important role in dealing with high dimensional statistical modelling. In this article, we study the variable selection of quadratic approximation via the smoothly clipped absolute deviation (SCAD) penalty with a diverging number of parameters. We provide a unified method to select variables and estimate parameters for various of high dimensional models. Under appropriate conditions and with a proper regularization parameter, we show that the estimator has consistency and sparsity, and the estimators of nonzero coefficients enjoy the asymptotic normality as they would have if the zero coefficients were known in advance. In addition, under some mild conditions, we can obtain the global solution of the penalized objective function with the SCAD penalty. Numerical studies and a real data analysis are carried out to confirm the performance of the proposed method.     

Confession Governance and Verdicts in China’s Criminal Justice

The objective phenomenon of reliance on confessions is the source of many problems in the practice of criminal justice in China. Although successive amendments to the law have endeavored to improve the handling of confessions, they have been unable to resolve the dilemma of a rigid management mode, incompatible management strategies, and conflicting attitudes towards management. This paper has made a multi-dimensional reinterpretation of it from the judges’ perspective, including functional analysis, cultural interpretation and immediate considerations. It reveals that behind its functions of offering moral comfort or allowing evasion of responsibility, confession, as a medium of physical and intellectual management, has the more important function of supplementing and improving the legitimacy of criminal verdicts. The remolding of the legitimacy of criminal verdicts with the coordinated improvement of the management of confessions will change the mode of association between those who currently govern confession and those they govern and will clash with the current closed mode of criminal justice management, thereby promoting a transformation in the governance of criminal justice.     

Transductive versions of the LASSO and the Dantzig Selector

Transductive methods are useful in prediction problems when the training dataset is composed of a large number of unlabeled observations and a smaller number of labeled observations. In this paper, we propose an approach for developing transductive prediction procedures that are able to take advantage of the sparsity in the high dimensional linear regression. More precisely, we define transductive versions of the LASSO (Tibshirani, 1996) and the Dantzig Selector (Candès and Tao, 2007). These procedures combine labeled and unlabeled observations of the training dataset to produce a prediction for the unlabeled observations. We propose an experimental study of the transductive estimators that shows that they improve the LASSO and Dantzig Selector in many situations, and particularly in high dimensional problems when the predictors are correlated. We then provide non-asymptotic theoretical guarantees for these estimation methods. Interestingly, our theoretical results show that the Transductive LASSO and Dantzig Selector satisfy sparsity inequalities under weaker assumptions than those required for the “original” LASSO.     

Into the IRIS: a model for analyzing identity dynamics in conflict

I propose a lens model for understanding how core identities (ethnic, sectarian, racial or national) are affected by past interactions and narratives increasing the chances of the outbreak of violent conflict. The model can be used to show how core identities are polarized during conflict escalation and how they might de-polarize during periods of de-escalation and conflict resolution, leading to potential transformation of core identities in post-conflict situations. Northern Ireland will be used to illustrate the Integrated Relational Identity Structure model, showing how conflicting identities have changed, or not, as a result of history, the conflict and the peace process.     

The Box–Cox Transformation and Non‐Iterative Estimation Methods for Ordinal Log‐Linear Models

Recently Beh and Farver investigated and evaluated three non‐iterative procedures for estimating the linear‐by‐linear parameter of an ordinal log‐linear model. The study demonstrated that these non‐iterative techniques provide estimates that are, for most types of contingency tables, statistically indistinguishable from estimates from Newton's unidimensional algorithm. Here we show how two of these techniques are related using the Box–Cox transformation. We also show that by using this transformation, accurate non‐iterative estimates are achievable even when a contingency table contains sampling zeros.     

From advocacy to service provision: state transformation and the disability rights movement in Taiwan

This research uses the development of the disability rights movement in Taiwan as a case study to analyze the impact of state transformation, in particular marketization of social welfare policy, on the disability rights movement. First, the institutionalization of the disability rights movement enabled it to expand its organizational structure and become involved in shaping policy. Secondly, when disability rights organizations started to undertake state-funded projects, their focus shifted from advocacy to service provision. Thirdly, competition for limited state-funding gave the organizations led by urban-middle class advocates a significant advantage over small, community-based NPOs and gathered significantly greater resources. Finally, this paper suggests that, in a context in which the state did not provide basic social services for its citizens with disabilities, the institutionalization of SMOs turned advocacy groups into service providers. Although the number of disability civic organizations increased, the voices of advocacy groups were weakened.     

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.     

知识产权“十二五”发展规划实施的关键难题与机遇研究

知识产权＂十二五＂发展规划具有多重属性与复杂性、制定组织结构多元化、地区发展不平衡及其与环境匹配较难等特点,较薄弱的知识产权基础因素与国际发展动态影响下,使得我国知识产权＂十二五＂发展规划实施挑战与机遇并存。     

阜新创建资源枯竭转型示范市生态建设的哲学思考

针对阜新市创建资源枯竭转型示范市过程中不能忽视生态建设这一现实问题,采用理论分析与现实结合的方法,论述了阜新市创建示范市生态建设的哲学依据、现实基础和建设措施,表明生态建设要以生态伦理学为哲学依托对阜新创建示范市有现实意义。     

Survival and lifetime data analysis with a flexible class of distributions

We introduce a general class of continuous univariate distributions with positive support obtained by transforming the class of two-piece distributions. We show that this class of distributions is very flexible, easy to implement, and contains members that can capture different tail behaviours and shapes, producing also a variety of hazard functions. The proposed distributions represent a flexible alternative to the classical choices such as the log-normal, Gamma, and Weibull distributions. We investigate empirically the inferential properties of the proposed models through an extensive simulation study. We present some applications using real data in the contexts of time-to-event and accelerated failure time models. In the second kind of applications, we explore the use of these models in the estimation of the distribution of the individual remaining life.