基于GWR模型的互联网对第三产业区域影响研究——以2012与2016年中国各省横截面数据为例

为探究互联网对第三产业发展的影响在各省区域上的空间相关性和空间异质性,以2012和2016年横截面数据为例,采用地理加权回归(GWR)模型进行实证分析。研究发现,互联网对第三产业的区域影响分布与区域要素禀赋关联,并受到产业集聚与产业分散的交互作用。新时期以知识溢出与社群经济为核心的"服务众包模式"兴起,用户参与等"人"的因素更加突出。最后,本文对当前政府政策的制定与互联网企业的发展提出了合理建议。     

一类污染数据回归模型参数的最大似然估计及若干不变性

摘要 本文研究一般的线性回归模型的观测向量受到一种污染时未知参数的最大似然估计,并讨论了若干用于统计推论的统计量在污染下的不变性。不变性的研究提示我们,在何种统计推断中可无视污染的影响。     

多元统计中的预测问题

对于回归模型，知道因变量的点估计意义并不是很大，我们还要它的预测精度，应该构造一个区间(T1，T2)，使对应于某个特定的实际值y0以1-α的概率被区间(T1，T2)所包含。本文对于多元的情况进行了推广。     

绵阳地区中山柏月生长量与自然条件关系的统计分析研究

利用相关分析与回归分析，对四川绵阳地区三年生中山柏月生长量与月均气温、月降雨量、月均日照时数、月均温度之间的关系进行初步的统计分析，并得到了相应的回归方程，从而揭示了影响中山柏生长量的最主要的相关因素．     

不同统计方法对跳高成绩分析的比较研究

以全回归、逐步回归、灰色关联和斜关联分析等方法，利用参考文献中的原始数据，对影响跳高成绩的因素重新进行分析，结果表明：尽管各种统计分析得出了一个大致的结论——助跑摸高是影响跳高成绩的主要因素，但是，各分析统计方法的结果都有不同程度的缺陷?这可能与样本含量的大小、统计方法的局限、优秀运动员技术的个性化特征及数据的信度有关。     

Class size effects on mathematics achievement in Cyprus: evidence from TIMSS

Class size reduction has been viewed as one school mechanism that can improve student achievement. Nonetheless, the literature has reported mixed findings about class size effects. We used 4th- and 8th-grade data from TIMSS 2003 and 2007 to examine the association between class size and mathematics achievement in public schools in Cyprus. We employ instrumental variables methods, and take advantage of a regression discontinuity design to examine causal effects of class size on mathematics achievement. The results indicate a non-significant relationship between class size and mathematics achievement in 8th grades. However, there is evidence of positive class size effects in 4th grade. The gender gap is significant and favoured males in 4th grade and females in 8th grade. SES indexes such as parental education and items in the home are positively and significantly related to mathematics achievement. Teacher and school variables are not significantly related with mathematics achievement.     

Ordinary Least Squares and Quantile Regression: An Inquiry-Based Learning Approach to a Comparison of Regression Methods

We present a short, inquiry-based learning course on concepts and methods underlying ordinary least squares (OLS), least absolute deviation (LAD), and quantile regression (QR). Students investigate squared, absolute, and weighted absolute distance functions (metrics) as location measures. Using differential calculus and properties of convex functions, students discover the sample mean, median, and pth quantile by minimizing sums of distances. Students use these metrics to define loss functions for OLS, LAD, and QR, and explore methods to minimize them. We discuss classroom experiences over two semesters. Classroom activities, Maple worksheets, and R demonstration code are available at a companion website.     

Student Hits in an Internet‐Supported Course: How Can Instructors Use Them and What Do They Mean?

The world of education is changing as Web‐based technology and courseware are increasingly used for delivery of course material. In this environment, instructors may need new measures for determining student involvement, and ultimately student performance. This study examines whether hits to a Web site have any value for predicting student performance in a traditional course supported by Web activities. Total Hits at the end of the semester was used as one measure. Hit Consistency, determined by assigning a 0 when no hits occurred between class meetings and by assigning a 1 when one or more hits occurred between class meetings, was another. Hit Consistency was significantly correlated with course average (r= .37, p < .001) for 108 students in two course sections. Hit Consistency started to show a significant relationship with course average by the third week (or class). Total Hits was not found to significantly correlate with course average (r= .08, p > .05) at the end of the semester or during any week. These results suggest that students who consistently access a Web site will perform better than those who do not. When Hit Consistency and Total Hits were entered as independent variables into a stepwise regression with course average as the dependent variable, the model was enhanced by the addition of Total Hits after Hit Consistency was entered (R= .43, p < .001) . Hierarchical regression analysis in which cumulative grade point average was entered as the first controlling variable suggested that online access may go beyond the predictive value of achievement alone for predicting course performance with Hit Consistency appearing to be the dominant causal variable.     

支持向量机在图像去噪处理中的初步研究

图像去噪是图像分割等操作的关键预处理环节,是从图像处理过度到图像分析和理解的重要手段之一,是图像处理中研究的重点内容.现有典型的一些图像去噪方法大多采用平滑滤波机理,在保护图像边缘信息等方面存在一定的局限性. 本文在对现有典型的图像去噪方法总结的基础上,提出了一种图像去噪的新方法--利用支持向量机(SVM)技术构建图像去噪滤波器,并在实现算法和实验仿真方面做了初步探讨.