团队反思对员工绩效影响的跨层次研究

通过建立跨层次的中介效应模型,运用多层线性模型方法,考察团队反思对员工绩效的影响。选取交互记忆系统和团队绩效两个中介变量,基于86个企业团队的数据进行实证研究,指出团队反思对员工绩效存在跨层次的影响,并且在此影响机制中交互记忆系统起到了中介作用,但团队绩效对员工绩效的直接影响效应不显著,即团队绩效对员工绩效无明显促进作用。     

The k-factor GARMA Process with Infinite Variance Innovations

In this article, we develop the theory of k-factor Gegenbauer Autoregressive Moving Average (GARMA) process with infinite variance innovations which is a generalization of the stable seasonal fractional Autoregressive Integrated Moving Average (ARIMA) model introduced by Diongue et al. (2008 Diongue, A.K., Guégan, D. (2008). Estimation of k-Factor GIGARCH Process: A Monte Carlo Study. Communications in Statistics-Simulation and Computation 37:2037–2049.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]). Stationarity and invertibility conditions of this new model are derived. Conditional Sum of Squares (CSS) and Markov Chains Monte Carlo (MCMC) Whittle methods are investigated for parameter estimation. Monte Carlo simulations are also used to evaluate the finite sample performance of these estimation techniques. Finally, the usefulness of the model is corroborated with the application to streamflow data for Senegal River at Bakel.     

计算机网络技术应用下的外语词汇教学模式研究

鉴于词汇教学在整个外语教学中的重要性及目前外语词汇教学所面临的问题,创建系统性外语词汇教学模式,并与计算机网络技术的应用相结合,来促进教师的外语词汇教学,进而提高学生的词汇学习效率。系统性外语词汇教学模式涉及三个主要教学阶段：课前预习、课堂教学和课后复习,而这三个教学阶段将与一系列新设计的词汇认知过程进行有机的结合。同时,还将尝试通过计算机网络技术的应用来优化新创建的系统性外语词汇教学模式。教师可以利用计算机网络技术为学生提供丰富的学习资源,并帮助他们充分运用各种词汇学习策略,从而调动学生对重点词汇学习的兴趣,进而提升教学效果。     

红军长征博物馆建于四川的原因

红军长征在四川历时最长,活动范围最广,斗争最复杂,创造的奇迹最多。红军在四川进行了卓有成效的地方工作,成立了四个省委,进行了民族政策的初步探索,而且还在大小金川、康区北部成立了两个省级少数民族革命政权。红军在与少数民族相处中,还留下许多佳话。中共中央在四川境内多次召开过关系党和国家命运的政治局会议及其它重要会议。在四川建立红军长征博物馆,可以通过发展红色旅游,重现长征历程,促进四川贫穷地区的经济文化发展。     

基于LW估计的中国证券市场长记忆性实证研究

针对国内研究证券市场长记忆性主要采用的是时域方法,文章采用基于频域的半参数Local Whittle估计方法研究了中国证券市场的长记忆特性,并且和对数周期图回归(GPH)方法进行了比较。结果表明,LW方法具有不受时间频率的影响,能够有效消除时间序列中短期记忆和周期性对估计结果的影响等优点,明显优于GPH方法。实证结果表明,中国证券市场存在明显的长记忆性,并且长记忆行为在重大突发事件发生期间更加明显。文章还从长记忆的角度探讨了“政策市”的存在性和相关特点。     

数字媒介视域下的文化记忆研究

文化记忆媒介经历多次嬗变,从口述媒介、书写媒介、印刷媒介到当下的数字媒介.媒介嬗变为文化记忆当下化提供了基本的结构框架,尤其是数字媒介,对文化记忆的储存、传播和表现产生了诸多新影响.首先,它极大地提升了文化记忆的储存能力,也产生了"数字黑暗时代"问题;其次,它有利于传播个体关于文化记忆的观点和评价,放大了各群体间关于文...     

对外汉语报刊语言的长句教学探索

报刊语言中长句多,留学生读起来吃力。长句不讲不明白,也可能越讲越糊涂。制订化长句繁难为简易的教学方略,采取单项训练与综合训练相结合的措施,坚持循环往复、加强重现螺旋式提高的原则,可以提高留学生阅读速度和语言交际能力。     

Practical Maximum Pseudolikelihood for Spatial Point Patterns(with Discussion)

This paper describes a technique for computing approximate maximum pseudolikelihood estimates of the parameters of a spatial point process. The method is an extension of Berman & Turner's (1992) device for maximizing the likelihoods of inhomogeneous spatial Poisson processes. For a very wide class of spatial point process models the likelihood is intractable, while the pseudolikelihood is known explicitly, except for the computation of an integral over the sampling region. Approximation of this integral by a finite sum in a special way yields an approximate pseudolikelihood which is formally equivalent to the (weighted) likelihood of a loglinear model with Poisson responses. This can be maximized using standard statistical software for generalized linear or additive models, provided the conditional intensity of the process takes an 'exponential family' form. Using this approach a wide variety of spatial point process models of Gibbs type can be fitted rapidly, incorporating spatial trends, interaction between points, dependence on spatial covariates, and mark information.     

Time‐change models for asymmetric processes

Many records in environmental sciences exhibit asymmetric trajectories. The physical mechanisms behind these records may lead for example to sample paths with different characteristics at high and low levels (up–down asymmetries) or in the ascending and descending phases leading to time irreversibility (front–back asymmetries). Such features are important for many applications, and there is a need for simple and tractable models that can reproduce them. In this paper, we explore original time‐change models where the clock is a stochastic process that depends on the observed trajectory. The ergodicity of the proposed model is established under general conditions, and this result is used to develop nonparametric estimation procedures based on the joint distribution of the process and its derivative. The methodology is illustrated on meteorological and oceanographic data sets. We show that, combined with a marginal transformation, the proposed methodology is able to reproduce important characteristics of the data set such as marginal distributions, up‐crossing intensity, and up–down and front–back asymmetries.