两部分混合回归模型的贝叶斯推断

两部分回归模型在刻画半连续型数据的概率发生机制具有重要作用.本文将经典的两部分回归模型推广到两部分有限混合模型,通过假定多条回归直线的混合来解释分布的不齐一性.在贝叶斯框架内,运用马尔可夫链蒙特卡洛(MCMC)方法来进行后验分析.Polya-Gamma先验被用来对logistic模型进行拟合,同时,Stick-breaking先验用于随机权.这些有助于加速后验抽样.本文对可卡因数据展开实证分析.     

超变异广义Logistic回归模型及其在分析授精数据中的应用(英文)

本文提出在超变异logistic回归模型中采用灵活的联系函数,文中研究了用统计程序包Genstat编写模型拟合程序的问题。我们把这一模型应用于人工授精试验数据的分析中,并对所得的结果与应用非超变异模型的结果进行了比较。     

在线Logistic回归

针对连续数据流分类问题,基于在线学习理论,提出一种在线logistic回归算法.研究带有正则项的在线logistic回归,提出了在线logistic-l2回归模型,并给出了理论界估计.最终实验结果表明,随着在线迭代次数的增加,提出的模型与算法能够达到离线预测的分类结果.本文工作为处理海量流数据分类问题提供了一种新的有效方法.     

非等间距GM(1,1)模型的改进与应用

将累积法引入非等间距GM(1,1)模型,得到累积法非等间距GM(1,1)模型.为了减少模型的滞后误差,引入一种可优化的背景值构造方法,将其代入累积法非等间距GM(1,1)模型的离散化方程,推导出可作为预测值计算公式的递推式,用来取代传统的白化响应式.结果分析表明累积法在非等间距模型中的应用效果良好,模型的拟合与预测精度都很高.     

Logistic回归中的加权最小二乘估计

本文引入因变量是虚拟变量的回归模型 ,并通过logistic函数拟合这种模型 ,分析它在控制和预测方面的不足之处 .在此基础上提出用加权最小二乘估计回归方程 .模拟结果表明 ,此方法是可行的     

删失数据下的半参数变系数部分线性回归模型

为了分析删失数据,该文考虑变系数部分线性模型,此模型允许协变量对响应变量存在非线性影响.响应变量与协变量之间关系的统计模型通过线性结构来拟合是非常重要而且有益.对于删失数据,常用的统计方法不能直接应用于此模型.该文首先提出一类数据变换用以建立无偏条件期望.然后利用profile最小二乘方法,给出了模型中参数分量和非参数分量的profile最小二乘估计,并建立了这些估计的渐近正态性.最后通过数值例子来说明该文所提出的方法的有效性.     

小波变换在期货价格序贯相关分析中的应用

针对金融时间序列普遍具有非平稳、自相关等特点,通常建立ARIMA模型进行识别.但模型的构建中,常受到一些随机扰动的影响,使模型拟合的误差增大.文章试将小波分析良好的局部性与ARIMA模型的简捷实用相结合,采用基于小波分析的累积式自回归滑动平均方法(WARIMA)拟合模型中的序贯相关,实证分析得出,WARIMA模型显著降低了拟合误差.     

局部权重调节的自适应惩罚样条回归模型

传统惩罚样条回归模型中的惩罚是均匀惩罚未考虑数据的局部异质性,因而对复杂数据的拟合缺乏自适应性.本文针对约束回归模型惩罚项的设置特点,设计一种局部惩罚权重向量并将其加入到模型中,构造基于B样条基的自适应惩罚样条回归模型.新模型在观测数据波动较大的区域,给予拟合曲线较小的惩罚,而在观测数据波动较小的区域,给予拟合曲线较大的惩罚,从而使拟合曲线能自适应的反映观测数据的局部变化特征.模拟和应用的结果显示新模型的拟合效果显著优于传统的惩罚样条回归模型.     

基于径向基的自适应惩罚样条回归模型

传统惩罚样条回归模型中惩罚项的设置未考虑数据的空间异质性,因而对复杂数据的拟合缺乏自适应性.文章通过对径向基函数的几何意义分析,以节点两侧相邻区域内数据点的纵向极差为基础,构造局部惩罚权重向量并加入到约束回归模型的惩罚项中,构造了基于径向基的自适应惩罚样条回归模型.新模型在观测数据波动较大的区域,给予拟合曲线较小的惩罚,而在观测数据波动较小的区域,给予拟合曲线较大的惩罚,从而使拟合曲线能自适应地反映观测数据的局部变化特征.模拟和应用结果显示新模型的拟合效果显著优于传统的惩罚样条回归模型.     

Kumaraswamy Binomial分布

在Binomial模型中考虑over-dispersion时,每一个独立事件成功的概率通常被视为一个连续随机变量.在本文中,我们提出了成功概率服从Kumaraswamy分布的混合Binomial模型.讨论了这个模型的随机序和相依性;并用数据来拟合这些模型,数值计算结果表明在拟合某些数据时KB模型比BB模型拟合效果更好.     

Supporting Middle School Teachers’ Implementation of STEM Design Challenges

We describe and analyze a professional development (PD) model that involved a partnership among science, mathematics and education university faculty, science and mathematics coordinators, and middle school administrators, teachers, and students. The overarching project goal involved the implementation of interdisciplinary STEM Design Challenges (DCs). The PD model targeted: (a) increasing teachers’ content and pedagogical content knowledge in mathematics and science; (b) helping teachers integrate STEM practices into their lessons; and (c) addressing teachers’ beliefs about engaging underperforming students in challenging problems. A unique aspect involved low‐achieving students and their teachers learning alongside each other as they co‐participated in STEM design challenges for one week in the summer. Our analysis focused on what teachers came to value about STEM DCs, and the challenges in and affordances for implementing DCs. Two significant areas of value for the teachers were students’ use of scientific, mathematical, and engineering practices and motivation, engagement, and empowerment by all learners. Challenges associated with pedagogy, curriculum, and the traditional structures of the schools were identified. Finally, there were four key affordances: (a) opportunities to construct a vision of STEM education; (b) motivation to implement DCs; (c) ambitious pedagogical tools; and, (d) ongoing support for planning and implementation. This article features a Research to Practice Companion Article . Please click on the supporting information link below to access.     

Are beginning calculus and engineering students adequately prepared for higher education? An assessment of students’ basic mathematical knowledge

Are students transitioning from the secondary level to university studies in mathematics and engineering adequately prepared for education at the tertiary level? In this study, we discuss the prior mathematical knowledge and skills demonstrated by Norwegian engineering (N?=?1537) and calculus (N?=?626) university students by using data from a mathematics assessment administered by the Norwegian Mathematical Council. The assessment examines students’ conceptual understanding, computation skills and problem solving skills on the basis of the mathematics curriculum of lower secondary education. We found that calculus students significantly outperformed engineering students, but both student groups struggled to solve the test, with the calculus and engineering groups scoring an average of 60% and 46%, respectively. Beginning students who fail to master basic skills, such as solving arithmetic and algebra problems, will most likely face difficulties in their further courses. Although few female students enrol in calculus and engineering programmes compared with male ones and are thus underrepresented, male and female students at the same ability level achieved comparable test scores. Furthermore, students reported high levels of intrinsic and extrinsic motivation, and a positive relationship was observed between intrinsic motivation and achievement.     

Leading Learning: Science Departments and the Chair

In this article, we have considered the role of the chair in leading the learning necessary for a department to become effective in the teaching and learning of science from a reformed perspective. We conceptualize the phrase “leading learning” to mean the chair's constitution of influence, power, and authority to intentionally impact the conceptual, pedagogical, cultural, and political aspects of teachers’ work. The data for this article are based on our ongoing work with one science department, over the past nine years, and have been woven into a longitudinal narrative study of a chair who has led the learning of an effective department since 2000. In considering the data, we can reach two major conclusions. First, for a chair to lead learning is to build a professional commitment to a vision of science education, not a particular program. Second, in leading learning, chairs afford opportunities for teacher empowerment. This affordance, however, is only half the issue. It is commitment to a vision that drives a desire to take advantage of opportunities as they arise. In leading learning that reflects changes in the broader science education community, learning opportunities are opened beyond the department.     

The relationship between mathematical problem-solving skills and self-regulated learning through homework behaviours,motivation, and metacognition

Studies highlight that using appropriate strategies during problem solving is important to improve problem-solving skills and draw attention to the fact that using these skills is an important part of students’ self-regulated learning ability. Studies on this matter view the self-regulated learning ability as key to improving problem-solving skills. The aim of this study is to investigate the relationship between mathematical problem-solving skills and the three dimensions of self-regulated learning (motivation, metacognition, and behaviour), and whether this relationship is of a predictive nature. The sample of this study consists of 323 students from two public secondary schools in Istanbul. In this study, the mathematics homework behaviour scale was administered to measure students’ homework behaviours. For metacognition measurements, the mathematics metacognition skills test for students was administered to measure offline mathematical metacognitive skills, and the metacognitive experience scale was used to measure the online mathematical metacognitive experience. The internal and external motivational scales used in the Programme for International Student Assessment (PISA) test were administered to measure motivation. A hierarchic regression analysis was conducted to determine the relationship between the dependent and independent variables in the study. Based on the findings, a model was formed in which 24% of the total variance in students’ mathematical problem-solving skills is explained by the three sub-dimensions of the self-regulated learning model: internal motivation (13%), willingness to do homework (7%), and post-problem retrospective metacognitive experience (4%).     

On the process of gaining language as a resource in mathematics education

In this paper, we expand our prior work on mathematics education in contexts of language diversity by elaborating on the three perspectives on language described by Ruiz (NABE J 8(2):15–34, 1984): language-as-right, language-as-resource, and language-as-problem. We illustrate our arguments with data taken from research contexts in Catalonia-Spain and South Africa. In these two parts of the world, the language policy in education has long been an issue, with a monolingual orientation that values one language (i.e., Catalan in Catalonia and English in South Africa) over others. Throughout the introduction of specific examples of policy documents, classroom practices, and participants’ reports, our main point is that the right of using the students’ languages makes sense because it is itself more than an intrinsic human right; it is an option that potentially benefits the creation of mathematics learning opportunities. Especially for the instances of classroom practices, our examples can be considered as representative in that they point to a common situation in our data: despite the fact of the language of learning and teaching being fixed, there is room for the learners and the teacher to take or react to a decision on what language to use, with whom, and how in concrete moments of the interaction. However, on the basis of our studies and drawing on the literature in mathematics education and language diversity, we argue that language rights are not sufficiently connected to language as a pedagogical resource. The enactment of these rights is still contributing in many ways to the social and political construction of problems concerning the role of certain languages in classroom interaction. We conclude the paper by discussing some possibilities for framing language as a resource that provide effective support to all students’ learning of mathematics.     

Action learning versus strategy learning

This article seeks to ascertain whether the strategy‐learning model of Hanaki, Sethi, Erev, and Peterhansl (2003) better accounts for observed behavior than do the various action‐learning models. It does so by measuring the goodness‐of‐fit of the models' predictions against published experimental results for such games as Coordination, Prisoner's Dilemma, and Chicken. The fit is measured via the mean squared deviation (MSD) between the observed behavior and the one predicted by the model. The results show that, for Chicken, the strategy‐learning model fits the observed data much better than do the action‐learning models. The best action‐learning model, on the other hand, fits the observed data well in Coordination. Overall, the strength of the strategy‐learning model is best shown in games where alternations between the two stage‐game Nash equilibria are often observed in the laboratory experiments. © 2004 Wiley Periodicals, Inc. Complexity 9: 41–50, 2004     

The Effects of Self-Regulation,Motivation, Anxiety,and Attributions on Mathematics Achievement for Fifth and Sixth Grade Students

For this quantitative study, a total of n = 761 students (58.1% female) from selected fifth- and sixth-grade mathematics classrooms in Alabama were surveyed in order to investigate the relationships between self-regulated learning, motivation, anxiety, attributions and achievement in mathematics. Data analyses revealed that significant contributions are made by motivation and anxiety on both test score and mathematics grade for fifth grade students. Specific factors (e.g., self-efficacy, worry, other, and failure) were related to academic performance while failure attribution was significantly related to mathematics grade. As for sixth grade students, data analyses showed relationships exist between motivation, anxiety and academic performance with specific factors (i.e., self-efficacy, intrinsic value, and worry) significantly predicting both test score and mathematics grade for sixth graders. The findings underlie the importance of motivation and anxiety for students and how these constructs interact to facilitate self-regulation over the course of developing expertise in a domain, such as mathematics.     

Differentiation of teaching and learning mathematics: an action research study in tertiary education

Diversity and differentiation within our classrooms, at all levels of education, is nowadays a fact. It has been one of the biggest challenges for educators to respond to the needs of all students in such a mixed-ability classroom. Teachers’ inability to deal with students with different levels of readiness in a different way leads to school failure and all the negative outcomes that come with it. Differentiation of teaching and learning helps addressing this problem by respecting the different levels that exist in the classroom, and by responding to the needs of each learner. This article presents an action research study where a team of mathematics instructors and an expert in curriculum development developed and implemented a differentiated instruction learning environment in a first-year engineering calculus class at a university in Cyprus. This study provides evidence that differentiated instruction has a positive effect on student engagement and motivation and improves students’ understanding of difficult calculus concepts.     

Putting People Back Into Science: Using Historical Vignettes

Current science education research reports that students do not embrace an understanding of the nature of science. Furthermore, few curriculum materials emphasize the nature of science. This paper suggests an effective technique for including the nature of science in existing courses. Using Wandersee's story form model, historical vignettes describe brief episodes from the lives of scientists. They are designed to take only about ten minutes of class time, provide content information, and promote examination of the nature of the scientific enterprise by generating discussion. They help students connect the present and past, show the evolution of the ideas they are learning, and make the information more interesting.     

Making Statistics Significant in a Short Course for Graduates with Widely-Varying Non-Statistical Backgrounds

With reference to a short compulsory module for MBA students, this paper discusses how, despite a range of pressures and an extraordinary range of student backgrounds, fears and motivations, it is possible to quickly facilitate understanding and confidence in handling data and basic statistics for graduates in business and associated workplaces. Links and contrasts with a variety of undergraduate teaching scenarios help to enrich teaching and learning strategies, and the strategies and materials developed through interaction with the range of MBA students are transferable to other postgraduate coursework situations. In particular, the need for understanding and confidence in handling data and its presentation, in considering categorical and simple continuous data, and in understanding correlation and association, are common across many different workplaces and applications.