On bates of convergence in the central limit theorem for parameter estimation in general autoregressive model

This paper explores the rate at which the estimates of the unknown parameters in an autoregressive process converge in distribution to the normal variate.     

The application of generalized ridge and stein-like general minimax rules to multicollinear data

We consider the use of minimax shrinkage estimators for the linear regression mcjel under several loss functions when severe multicollinearity is present. The examples considered illustrate that little or no departure from the least squares estimates is permitted in many cases when the data is highly multicollinear and/or shrinkage is toward a point in the parameter space that does not closely agree with the sample data     

Modelling and smoothing parameter estimation with multiple quadratic penalties

Penalized likelihood methods provide a range of practical modelling tools, including spline smoothing, generalized additive models and variants of ridge regression. Selecting the correct weights for penalties is a critical part of using these methods and in the single-penalty case the analyst has several well-founded techniques to choose from. However, many modelling problems suggest a formulation employing multiple penalties, and here general methodology is lacking. A wide family of models with multiple penalties can be fitted to data by iterative solution of the generalized ridge regression problem minimize || W ^1/2 ( Xp − y ) ||²ρ+Σ _{i =1} ^m  θ _i p ' S _i p ( p is a parameter vector, X a design matrix, S _i a non-negative definite coefficient matrix defining the i th penalty with associated smoothing parameter θ _i , W a diagonal weight matrix, y a vector of data or pseudodata and ρ an 'overall' smoothing parameter included for computational efficiency). This paper shows how smoothing parameter selection can be performed efficiently by applying generalized cross-validation to this problem and how this allows non-linear, generalized linear and linear models to be fitted using multiple penalties, substantially increasing the scope of penalized modelling methods. Examples of non-linear modelling, generalized additive modelling and anisotropic smoothing are given.     

Flexible empirical Bayes estimation for wavelets

Wavelet shrinkage estimation is an increasingly popular method for signal denoising and compression. Although Bayes estimators can provide excellent mean-squared error (MSE) properties, the selection of an effective prior is a difficult task. To address this problem, we propose empirical Bayes (EB) prior selection methods for various error distributions including the normal and the heavier-tailed Student t -distributions. Under such EB prior distributions, we obtain threshold shrinkage estimators based on model selection, and multiple-shrinkage estimators based on model averaging. These EB estimators are seen to be computationally competitive with standard classical thresholding methods, and to be robust to outliers in both the data and wavelet domains. Simulated and real examples are used to illustrate the flexibility and improved MSE performance of these methods in a wide variety of settings.     

英语短语动词语义扩展的认知理据

英语动词短语被广泛地认为难以掌握因为动词和小品词的组合似乎无理可循。过去一直认为它们是任意组合起来的语言现象,只能通过死记硬背的方法来学习。然而,认知语言学却认为动词短语的组合是有理据的,可以分析并加以系统化。文章援用认知语言学中的原型范畴、理想认知模型及认知域、意象图式、概念隐喻等几个经典理论,具体探讨了短语动词语义延伸的认知理据,进而阐明小品词在建构短语动词时的原理,为短语动词理解提供了认知理据。     

低碳试点政策对生态效率的影响及溢出效应--基于空间双重差分的实证分析

全面准确地评估低碳城市试点的政策效应,对于进一步推进城市生态文明建设具有重要意义。本文基于2007—2019年209个城市的面板数据,利用第二批低碳城市试点作为一项准自然实验,运用空间双重差分模型评估了低碳试点政策对城市生态效率产生的本地效应和空间溢出效应。研究发现,低碳试点政策不仅显著提高了试点城市的生态效率,而且对周边城市的生态效率产生了正向的溢出效应。中介机制分析表明低碳试点政策主要通过技术创新效应和产业结构效应促进了试点城市生态效率的提升。异质性分析结果表明低碳试点政策在西部地区的政策效应最大,低碳试点政策仅在东部地区产生了显著为正的溢出效应。     

高校双语教学效果的心理影响因素研究

从学生心理层面出发,基于结构方程模型（SEM）构建了高校双语教学效果心理影响因素理论模型。对该模型进行拟合验证后发现,影响高校双语教学效果的心理因素主要包括学习态度、学习兴趣、学习动机以及认知差异等方面。其中,学习态度对于双语教学效果的影响最为重要。     

城市居民金融社会化水平测度研究

金融社会化发展已成为当今金融发展的一个重要趋势,越来越多的普通百姓更加关注金融时事,参与金融活动。本文通过对陕西省西安市居民金融知识、金融意识、金融行为与金融外部环境的实证研究,得出居民年龄、学历、职业与性别对居民金融社会化有一定的影响;并利用Probit模型分析了这些因素对城市居民金融社会化发展的影响大小。最后,针对性的提出发展金融社会化的政策建议。     

关系资产与中非间贸易:基于40国面板数据的实证研究

中非间长期友好关系是否产生贸易促进效应是双方外交关系可持续性及各自应对外部冲击能力的重要支撑,基于中非间较同质化的外交关系资产背景,通过引入弱惩罚和强惩罚机制的关系持续期和以外交关系等级衡量的投资强度变量来测度关系资产,以克服外交活动与贸易间存在的内生性问题,并纳入冲突力对中非间关系的影响,并利用2001～2017年非洲40国贸易数据构建面板校正误差模型,考察中非国家间关系资产对双边贸易及细分初级产品和制成品贸易是否存在促进效应。研究表明,关系资产对中非贸易有显著促进作用,但存在两个相反的关系资产对贸易影响机制,即关系持续期作为非纯公共产品的贸易促进作用和对较大经济规模国家的贸易摊薄效应;中国经济增长对中非双向出口贸易有较强带动作用,对非洲国家关税减免政策具有互惠特征,对中非双边贸易均有明显促进作用,但对不同细分品类具有差异化影响;中国和非洲国家应合力提升关系投资强度,以进一步发挥惯性力和国家间关系的贸易提升力作用,以贸易促进支撑中非全面战略合作伙伴关系的发展。     

转型期社会信任的影响机制——市场化、个人资本与社会交往因素探讨

本文利用中国综合社会调查(CGSS)2005年的数据,基于因子分析将社会信任区分为强社会联系、一般社会联系和弱社会联系三个不同维度的信任,通过结构方程模型考察了市场化、个人资本与社会交往对社会信任的影响机制。研究结果表明,个人资本对上述三个维度的信任均没有显著影响,这否定了王绍光等人的新理性解释模型,说明信任不是个体层面的问题,而是社会层面的问题。市场化对强社会联系的信任没有影响,但是对一般社会联系和弱社会联系的信任均有显著的影响,但信任度提高不大。这说明市场化扩大了人际信任的范围,有利于提高整体社会的信任度。研究结果还表明,无论是熟人间的社会交往还是社团性的社会交往对社会信任都有显著的影响,且影响较大,这表明社会信任正是在社会互动中生产出来的。人际交往的范围扩大和频率增加,有望提高整体社会的信任度。