新课程下的教育评价：趋势与走向

论文结合国内外正在进行的评价实践,提出了新课程背景下教育评价新的发展趋势和走向:在评价主体上呈现出主客体之间渗透的互动过程;在评价目标上强调鉴别性与导向性并重;在评价方法上注重质性与量化之间融合的多元化走向;在评价途径上突出目标性和过程性的结合。     

The Robustness of Trend Stationarity: An Illustration with the Extended Nelson-Plosser Dataset

We re-evaluate Andreu and Spanos's findings in favour of trend stationarity by considering the extended Nelson-Plosser data set. This expanded (to 1988) data set includes a period of rather different behaviour compared with the original Nelson-Plosser data used by Andreou and Spanos. We find that Andreou and Spanos's models (with only minor adjustments) exhibit remarable stability over this extended period, and indicate that their conclusions are more robust than they have shown.     

论职工持股制度的深化与发展

农村包产到户,城市职工持股”是中国经济体制改革的两种基本模式。在企业产权制度改革中,应大力发展职工持股制度,明确发展思路与重点,规范职工持股制度的运作与管理。     

A bayesian estimator for the dependence function of a bivariate extreme‐value distribution

Any continuous bivariate distribution can be expressed in terms of its margins and a unique copula. In the case of extreme‐value distributions, the copula is characterized by a dependence function while each margin depends on three parameters. The authors propose a Bayesian approach for the simultaneous estimation of the dependence function and the parameters defining the margins. They describe a nonparametric model for the dependence function and a reversible jump Markov chain Monte Carlo algorithm for the computation of the Bayesian estimator. They show through simulations that their estimator has a smaller mean integrated squared error than classical nonparametric estimators, especially in small samples. They illustrate their approach on a hydrological data set.     

基于局部社团结构平衡的双模符号网络链路预测研究

随着互联网产业的高速发展,双模符号网络已经成为一类常见的复杂网络,然而针对此 类网络的分析较少。本文在传统非符号网络局部社团理论和符号网络结构平衡理论的基础上,首次提出了双模符号网络下的局部社团理论。这一理论不仅考虑了符号网络中共同邻居的信息,还引入了共同邻居间存在的连接。进一步地,本文推导出符号网络中基于局部社团信息的加权平衡回路增益指数,该指标可以表示双模符号网络中用户节点和产品节点间的符号关系。为了将该指标更好地应用于双模 符号网络链路预测问题,本文提出了加权平衡回路增益分类器算法。实验结果表明,相比其他经典链路预测算法,新算法具有更好的预测能力。     

Trend smoothness achieved by penalized least squares with the smoothing parameter chosen by optimality criteria

This work presents a study about the smoothness attained by the methods more frequently used to choose the smoothing parameter in the context of splines: Cross Validation, Generalized Cross Validation, and corrected Akaike and Bayesian Information Criteria, implemented with Penalized Least Squares. It is concluded that the amount of smoothness strongly depends on the length of the series and on the type of underlying trend, while the presence of seasonality even though statistically significant is less relevant. The intrinsic variability of the series is not statistically significant and its effect is taken into account only through the smoothing parameter.     

Coversge probabilty to the original data by prediction intervals in simple linear regression

The coverage rate of the original data by the prediction interval in simple linear regression is obtained by computer simulation. The results show that for small sample size, the coverage rate is higher than the assigned prediction coverage rate (confidence level). The two coverage rates begin to converge when the sample size is larger than 50 and the convergence rate depends very little on the distribution of the independent variable. Also, theoretical results on the asymptotic coverage rate and on the absolute minimum bounds are obtained     

中国城镇新增住房需求规模的测算与分析

本文围绕城镇家庭户自然增长、城镇家庭户机械增长和城镇存量住房拆除三项需求来源,设计了基于人口普查等公开统计数据定量测算城镇新增住房需求规模的系统性方法,对2001—2010年和2011—2015年间全国和各省份城镇新增住房需求规模进行测算与分析。在此期间新增住房供需关系经历了从基本均衡向供过于求的变化,同时存量住房拆除引致的被动需求取代城镇家庭户自然增长和机械增长引致的主动需求,成为新增住房需求的最主要来源。东、中、西部省份在新增需求规模、新增供需比、需求结构等方面表现出明显差异。本文还进一步对2021—2030年的发展趋 势进行了定量预测。由于三项需求来源均趋于下降,2021—2025年和2026—2030年间全国年均城镇新增住房需求规模预计将较2011—2015年间分别下降33%和53%。本文设计的城镇新增住房需求规模测算方法和预测思路能够为各级政府“十四五”住房发展规划编制、房地产企业战略制定等提供参考。     

金融市场收益率方向预测模型研究———基于文本大数据方法

金融市场的发展关系着一国的经济命脉,而股票市场作为金融市场的重要组成部分,对其收益率的研究也一直都是学术界的热点。财经新闻常被认为蕴含着丰富的信息,其中所包含的情感信息作为影响投资者投资决策的重要因素之一,对股票收益率也具有一定的影响。故本文构建了适用于金融投资领域的财经新闻情感词典来对财经新闻进行文本分析,同时构造了新的预测模型:将财经新闻文本中所含的情感量化为情绪指数并与时变密度函数相结合,得到时变加权密度模型。并在此基础上以模型评分为权重组合多个预测模型构建出评分加权模型用于股票收益率预测。结果显示,加入情绪指数能有效提高模型预测能力,而评分加权模型的预测能力则在此基础上更进一步,在准确率以及评分规则上基本达到双重最优。     

岩石可钻性能量法现场实验研究

本文介绍了岩石可钻性能全法在油田现场实脸研究的成果:确定其可钻性指标凡对地层的适用范围，证明K指标比其他可钻性指标能更容易、史好地反映出井下实际地层可钻性变化情无，用K指标预浏钻速与实际钻速接近.