A Necessary Condition for the Strong Oracle Property

A problem of using a non‐convex penalty for sparse regression is that there are multiple local minima of the penalized sum of squared residuals, and it is not known which one is a good estimator. The aim of this paper is to give a guide to design a non‐convex penalty that has the strong oracle property. Here, the strong oracle property means that the oracle estimator is the unique local minimum of the objective function. We summarize three definitions of the oracle property – the global, weak and strong oracle properties. Then, we give sufficient conditions for the weak oracle property, which means that the oracle estimator becomes a local minimum. We give an example of non‐convex penalties that possess the weak oracle property but not the strong oracle property. Finally, we give a necessary condition for the strong oracle property.     

Visualization for Large‐scale Gaussian Updates

In geostatistics and also in other applications in science and engineering, it is now common to perform updates on Gaussian process models with many thousands or even millions of components. These large‐scale inferences involve modelling, representational and computational challenges. We describe a visualization tool for large‐scale Gaussian updates, the ‘medal plot’. The medal plot shows the updated uncertainty at each observation location and also summarizes the sharing of information across observations, as a proxy for the sharing of information across the state vector (or latent process). As such, it reflects characteristics of both the observations and the statistical model. We illustrate with an application to assess mass trends in the Antarctic Ice Sheet, for which there are strong constraints from the observations and the physics.     

A Proportional Hazards Regression Model for the Subdistribution with Covariates‐adjusted Censoring Weight for Competing Risks Data

With competing risks data, one often needs to assess the treatment and covariate effects on the cumulative incidence function. Fine and Gray proposed a proportional hazards regression model for the subdistribution of a competing risk with the assumption that the censoring distribution and the covariates are independent. Covariate‐dependent censoring sometimes occurs in medical studies. In this paper, we study the proportional hazards regression model for the subdistribution of a competing risk with proper adjustments for covariate‐dependent censoring. We consider a covariate‐adjusted weight function by fitting the Cox model for the censoring distribution and using the predictive probability for each individual. Our simulation study shows that the covariate‐adjusted weight estimator is basically unbiased when the censoring time depends on the covariates, and the covariate‐adjusted weight approach works well for the variance estimator as well. We illustrate our methods with bone marrow transplant data from the Center for International Blood and Marrow Transplant Research. Here, cancer relapse and death in complete remission are two competing risks.     

Functional Partial Linear Single‐index Model

This paper deals with the problem of predicting the real‐valued response variable using explanatory variables containing both multivariate random variable and random curve. The proposed functional partial linear single‐index model treats the multivariate random variable as linear part and the random curve as functional single‐index part, respectively. To estimate the non‐parametric link function, the functional single‐index and the parameters in the linear part, a two‐stage estimation procedure is proposed. Compared with existing semi‐parametric methods, the proposed approach requires no initial estimation and iteration. Asymptotical properties are established for both the parameters in the linear part and the functional single‐index. The convergence rate for the non‐parametric link function is also given. In addition, asymptotical normality of the error variance is obtained that facilitates the construction of confidence region and hypothesis testing for the unknown parameter. Numerical experiments including simulation studies and a real‐data analysis are conducted to evaluate the empirical performance of the proposed method.     

土地股份合作社内部能形成利益联结机制吗？

土地股份合作社在促进资本与农地结合,实现小农户与现代农业衔接上具有独特优势。通过对普通社员与核心社员在土地股份合作社不同发展阶段的可选策略的讨论,分析合作社不同发展阶段利益联结机制的特征,并对黑龙江省齐齐哈尔市克山县仁发合作社的利益联结机制进行案例研究后提出:土地股份合作社坚持“退社自由”原则有利于保护普通社员的基本权益,但不利于在合作社内部形成“风险共担”机制,要在保证普通社员基本权益的同时建立“利益共享、风险共担”的利益联结机制,应该充分利用计提公积金这一手段,不允许社员退社时退回公积金或许是有利于土地股份合作社内部形成“风险共担”机制的一个可尝试的方法。     

我国中西部机场特征分析及其竞争力评价研究

首先对我国中西部机场的现状及其在未来发展建设中的优势进行了深入分析,并在此基础上提出了机场竞争力评价指标体系。其次,采用层次分析法和熵值法的组合赋权方法确定评价指标权重,并采用可拓学中的物元模型建立了机场竞争力评价模型,提出了一套科学合理、切实可行的机场竞争力评价方法。最后,以内蒙古机场集团7家机场为例进行了实证研究。     

宋代城隍神赐额封爵考释

宋代是城隍神信仰迅速发展的时期,北宋末年至整个南宋时期,朝廷通过对城隍神的封爵赐额这一手段对其加以控制和管理,使得宋代城隍神的官方化色彩和人格化形象深入人心,并影响到了元明城隍神信仰的发展.     

中国新诗发生与现代媒体

现代性存在于历史的时空里并且作为一个历史的过程演进着。文学的现代性研究差不多已成为时髦而老调的话题,其缺失之一在于研究的空泛无着。中国文学由古典型态转化为现代型态,或者说中国文学现代文体的发生,原本是多种合力共同作用的结果。文体的现代性是文学现代性重要的可感存在。媒体,作为一个较为具体的视窗,由此可观览中国现代文体发生的图景。中国现代文体的发生不仅提供了物化的条件,而且由于媒体生态关联性的影响,使得基于媒体的文体在形态与精神等方面,生成了异于过往的诸多质性。媒体对于中国现代文体发生的意义颇多。通过媒体这一视角,解析诗歌、散文、小说、戏剧四种文体,无疑是研究中国文学现代转型的具体路径和方法。     

霍华德政府时期澳大利亚移民人口结构变化及其社会影响——多元文化主义的视角

作为一个拥有悠久移民历史的国家,移民问题贯穿在澳大利亚历史上的每一个篇章中,而霍华德政府时期的移民人口结构则奠定了当代澳大利亚移民人口结构的基本形态,因此研究霍华德政府时期的移民人口结构更有助于认识当代澳大利亚社会。本文从回顾澳大利亚的移民历史着手,分别从移民的类别与年龄、来源国、性别结构、地区分布、受教育水平与英语水平这五方面来研究霍华德政府时期移民人口结构的特点,探寻移民人口结构变化对澳大利亚社会产生的诸多影响。