企业员工工作不安全感与组织承诺—— 领导——部属交换关系的调节效应研究

工作不安全感是工作中的一项重要压力来源,将导致员工一系列消极的组织态度与行为,因此对调节工作不安全感影响效应的相关变量的探索是近期该领域的研究热点。本文运用问卷调查法和调节层级回归分析方法,着重考察了领导—部属交换关系在工作不安全感与组织承诺之间的调节效应。研究结果表明:在质量性工作不安全感对情感承诺的消极影响中以及数量性工作不安全感对继续承诺的积极影响中,领导—部属交换关系均起到了正向的调节作用。     

明代格调派诗学所遗留的矛盾与问题辨析

格调论为明代诗学的主流与正宗,明代格调派强调格调优先,从形式入手,采取了一种"倒学"的方式,这种思维模式的先天缺陷,致使明代格调论产生了诸多难以克服的矛盾,诸如强调形式,忽视诗歌内容;"师匠宜高"与"捃拾宜博"的矛盾;才情的恣意张扬与拘囿规矩之间的冲突;"正"变"之间无所适从的尴尬;标扬神完气畅、卓立遒劲的雄浑格调,却又拒斥格偏调弱、恬适淡远的神韵诗风;恪守"拟议"之典则而难以"轩翥出辙"成其"变化"。     

让步条件句“即使p也q”的量级性

使用一个多维度量级模型来解释"即使p也q"的量级意义和句子的生成,并指出量级差异的本质是常规关系和非常规关系的不同。这可以解释两类特殊的"即使p也q"句:条件肯否对立句和假性反蕴涵句,从而证明量级性是"即使p也q"核心语义之一。     

《西游记》中存现句的运用及语用价值

《西游记》是中国四大古典名著之一,本文对《西游记》中存现句的运用情况进行了统计分析。总结了存现句在作品中运用的典型环境,分别是处所描写、人物描写和综合描写。而存现句的主要功能是对环境的描写,因此当各章节中环境描写较突出时,存现句就会较多,反之则较少。     

论书法艺术的自觉与楷书的产生

魏晋时期是中国艺术自觉的时期,也是书法艺术成熟的时期,而楷书也是在魏晋南北朝时期形成并走向成熟的。楷书的形成虽然是由文字发展过程中的简易律、区别律所决定的,但也与当时书法艺术的自觉有着极大的关系。楷书形体方正,笔画形态异常丰富,超越了之前的各种字体,书写方式比篆书、隶书多了许多连贯动作,这些方面正是书法艺术对楷书的形成所产生的影响。书法艺术的影响使楷书无论是在形体、笔画还是书写方式上都与之前的小篆、隶书等字体有很大的不同。     

以科学发展观为指导 加快合格本科院校建设——浙江树人大学本科建设的实践与认识

民办专科院校升格为本科院校，是民办高等教育的一大发展。本文在浙江树人大学本科建设实践的基础上，对民办本科院校建设的经验进行了总结，对部分向民办本科院校过渡的民办专科院校有一定的参考价值。     

On hypothesis testing for Poisson processes: Regular case

ABSTRACT

We consider the problem of hypothesis testing in the situation when the firsthypothesis is simple and the second one is local one-sided composite. We describe the choice of the thresholds and the power functions of the Score Function test, of the General Likelihood Ratio test, of the Wald test, and of two Bayes tests in the situation when the intensity function of the observed inhomogeneous Poisson process is smooth with respect to the parameter. It is shown that almost all these tests are asymptotically uniformly most powerful. The results of numerical simulations are presented.     

普通高校学生心理健康教育面临的新形势及对策

随着社会的发展,普通高校学生的心理问题日益突出,暴力行为屡见不鲜,已经成为社会关注和讨论的焦点。本文从导致普通高校学生日益突出的心理问题的原因分析入手,提出了深入开展大学生心理健康教育的对策。     

Size distributions reconsidered

We consider tests of the hypothesis that the tail of size distributions decays faster than any power function. These are based on a single parameter that emerges from the Fisher–Tippett limit theorem, and discriminate between leading laws considered in the literature without requiring fully parametric models/specifications. We study the proposed tests taking into account the higher order regular variation of the size distribution that can lead to catastrophic distortions. The theoretical bias corrections realign successfully nominal and empirical test behavior, and inform a sensitivity analysis for practical work. The methods are used in an examination of the size distribution of cities and firms.     

Direct estimation of differential networks under high-dimensional nonparanormal graphical models

In genomics, it is often of interest to study the structural change of a genetic network between two phenotypes. Under Gaussian graphical models, the problem can be transformed to estimating the difference between two precision matrices, and several approaches have been recently developed for this task such as joint graphical lasso and fused graphical lasso. However, the multivariate Gaussian assumptions made in the existing approaches are often violated in reality. For instance, most RNA-Seq data follow non-Gaussian distributions even after log-transformation or other variance-stabilizing transformations. In this work, we consider the problem of directly estimating differential networks under a flexible semiparametric model, namely the nonparanormal graphical model, where the random variables are assumed to follow a multivariate Gaussian distribution after a set of monotonically increasing transformations. We propose to use a novel rank-based estimator to directly estimate the differential network, together with a parametric simplex algorithm for fast implementation. Theoretical properties of the new estimator are established under a high-dimensional setting where $p$ grows with $n$ almost exponentially fast. In particular, we show that the proposed estimator is consistent in both parameter estimation and support recovery. Both synthetic data and real genomic data are used to illustrate the promise of the new approach. The Canadian Journal of Statistics 48: 187–203; 2020 © 2019 Statistical Society of Canada