我国“放管服”改革成效评估与展望

目的/意义 近年来,“放管服”改革已成为学术界研究的热点主题,十九大的胜利召开对“放管服”改革也提出了新的要求和指导建议。因此,系统梳理和比较国内“放管服”改革研究状况,对今后“放管服”改革的理论与实践推进具有重要意义。 设计/方法 选取国内“放管服”改革研究的重要期刊文献,对比分析十九大召开前后国内“放管服”改革研究的整体发展现状及研究内容差异。 结论/发现 十九大召开前后“放管服”改革的研究热点主题存在“差异多、共性少”的特点,而研究团队则表现为“共性多、差异少”,研究内容则呈现出“大同小异”的高度一致性特点。从内涵和问题优化上看,前后阶段表现为“共性少、差异多”;而从实践模式及效果评价上看,前后阶段表现为继承与发扬的关系,后阶段研究是对前期研究的持续深入推进。最后,从强化研究团队间的沟通合作,深入推进案例和实证研究,增加定性与定量相结合的混合研究三个方面提出未来研究展望。     

李白卒年新论

李白的卒年,依据李阳冰、范传正所记的李白生年和李华所记的李白享年即可确定为大历元年。从曾巩到王琦,对此提出了异议。但他们所提出的依据没有一条是信实可靠的,包括他们认作铁证的《为宋中丞自荐表》,编在至德二载也是不可靠的。要正确地确定李白的卒年,还是要回到李阳冰、范传正和李华那里去。     

19世纪末20世纪初中国商人阶层的崛起

在漫长的中国封建社会中,商业被贬之日末务,商人也位于四民之末,士农工商的地位归序似乎成了中国封建社会亘古不变的模式.然而到了19世纪末20世纪初,随着民族危机日益加深,商战呼之欲出,商人团体相继成立,商会诞生,商人政治意识提高并且对政治广泛参与,使商人的社会地位发生了根本性的变化.商人阶层坚持不懈地努力终于迎来了清政府自上而下的重商措施的出台.清延设立商部以指导商人组织,制定商律以规范商人行动,颁行一系列工商的法规以奖商恤商,一系列新经济政策的实施使社会舆论开始从抑商转为誉商,商人在社会上广受赞扬,官员也开始纷纷投资经商.所有这些,促进了中国新的绅商阶层的形成,并进而带动了整个商人阶层随之崛起.     

英语俚语汉译初探

英语俚语难以辨认和理解,因而在翻译中其意义和风格难以得以充分传达。为了保证其意义和风格在译文中充分再现,译者必须准确理解原文,再现原文特色以及说话者的个性     

综合业务CATV网络

本文提出了一种宽带分布式网络设计,该网络能在CATV电缆上同时进行数据、实时数字话音及模拟电视通信。本系统能支持大量用户间的通信。由于采用了宽带技术和总线网令牌与CSMA/CD的混合协议,从而解决了局域网所面临的距离和时延问题。本文最后对所提出网络的话音性能作了评估,所得结果与相关试验报导数据相符。     

Measuring non-linear dependence for two random variables distributed along a curve

We propose new dependence measures for two real random variables not necessarily linearly related. Covariance and linear correlation are expressed in terms of principal components and are generalized for variables distributed along a curve. Properties of these measures are discussed. The new measures are estimated using principal curves and are computed for simulated and real data sets. Finally, we present several statistical applications for the new dependence measures.     

我国行业分类与国际标准行业分类的比较研究

 本文通过对我国行业分类和国际标准行业分类两项分类标准最新版本的比较,对两项分类的基本构成、应用原则、门类和大类的条目结构以及对照转换等方面的情况进行了比较分析研究。详细解析了在若干行业领域中,二者存在典型差异的情况。最后,对我国的行业分类的科学性和国际可比性做出了分析评价,对如何进一步提升分类水平提出了改进意见,另外还提出了未来修订的思路和方法等建议。     

Central Limit Theorem approximations for the number of runs in Markov-dependent binary sequences

We consider Markov-dependent binary sequences and study various types of success runs (overlapping, non-overlapping, exact, etc.) by examining additive functionals based on state visits and transitions in an appropriate Markov chain. We establish a multivariate Central Limit Theorem for the number of these types of runs and obtain its covariance matrix by means of the recurrent potential matrix of the Markov chain. Explicit expressions for the covariance matrix are given in the Bernoulli and a simple Markov-dependent case by expressing the recurrent potential matrix in terms of the stationary distribution and the mean transition times in the chain. We also obtain a multivariate Central Limit Theorem for the joint number of non-overlapping runs of various sizes and give its covariance matrix in explicit form for Markov dependent trials.     

An exact density-based empirical likelihood ratio test for paired data

The Wilcoxon rank-sum test and its variants are historically well-known to be very powerful nonparametric decision rules for testing no location difference between two groups given paired data versus a shift alternative. In this title, we propose a new alternative empirical likelihood (EL) ratio approach for testing the equality of marginal distributions given that sampling is from a continuous bivariate population. We show that in various shift alternative scenarios the proposed exact test is superior to the classic nonparametric procedures, which may break down completely or are frequently inferior to the density-based EL ratio test. This is particularly true in the cases where there is a nonconstant shift under the alternative or the data distributions are skewed. An extensive Monte Carlo study shows that the proposed test has excellent operating characteristics. We apply the density-based EL ratio test to analyze real data from two medical studies.     

Nenparametric Two-Group Classification: Concepts and a SAS-Based Software Package

This article introduces BestClass, a set of SAS macros, available in the mainframe and workstation environment, designed for solving two-group classification problems using a class of recently developed nonparametric classification methods. The criteria used to estimate the classification function are based on either minimizing a function of the absolute deviations from the surface which separates the groups, or directly minimizing a function of the number of misclassified entities in the training sample. The solution techniques used by BestClass to estimate the classification rule use the mathematical programming routines of the SAS/OR software. Recently, a number of research studies have reported that under certain data conditions this class of classification methods can provide more accurate classification results than existing methods, such as Fisher's linear discriminant function and logistic regression. However, these robust classification methods have not yet been implemented in the major statistical packages, and hence are beyond the reach of those statistical analysts who are unfamiliar with mathematical programming techniques. We use a limited simulation experiment and an example to compare and contrast properties of the methods included in Best-Class with existing parametric and nonparametric methods. We believe that BestClass contributes significantly to the field of nonparametric classification analysis, in that it provides the statistical community with convenient access to this recently developed class of methods. BestClass is available from the authors.