Review: Reversed low-rank ANOVA model for transforming high dimensional genetic data into low dimension

A general modeling procedure for analyzing genetic data is reviewed. We review ANOVA type model that can handle both the continuous and discrete genetic variables in one modeling framework. Unlike the regression type models which typically set the phenotype variable as a response, this ANOVA model treats the phenotype variable as an explanatory variable. By reversely treating the phenotype variable, usual high dimensional problem is turned into low dimension. Instead, the ANOVA model always includes interaction term between the genetic locations and phenotype variable to find potential association between them. The interaction term is designed to be low rank with the multiplication of bilinear terms so that the required number of parameters is kept in a manageable degree. We compare the performance of the reviewed ANOVA model to the other popular methods via microarray and SNP data sets.     

Omega model for a jump–diffusion process with a two-step premium rate

In this paper, a jump–diffusion Omega model with a two-step premium rate is studied. In this model, the surplus process is a perturbation of a compound Poisson process by a Brown motion. Firstly, using the strong Markov property, the integro-differential equations for the Gerber–Shiu expected discounted penalty function and the bankruptcy probability are derived. Secondly, for a constant bankruptcy rate function, the renewal equations satisfied by the Gerber–Shiu expected discounted penalty function are obtained, and by iteration, the closed-form solutions of the function are also given. Further, the explicit solutions of the Gerber–Shiu expected discounted penalty function are obtained when the individual claim size is subject to exponential distribution. Finally, a numerical example is presented to illustrate some properties of the model.     

Evaluation of missing data mechanisms in two and three dimensional incomplete tables

The analysis of incomplete contingency tables is a practical and an interesting problem. In this paper, we provide characterizations for the various missing mechanisms of a variable in terms of response and non-response odds for two and three dimensional incomplete tables. Log-linear parametrization and some distinctive properties of the missing data models for the above tables are discussed. All possible cases in which data on one, two or all variables may be missing are considered. We study the missingness of each variable in a model, which is more insightful for analyzing cross-classified data than the missingness of the outcome vector. For sensitivity analysis of the incomplete tables, we propose easily verifiable procedures to evaluate the missing at random (MAR), missing completely at random (MCAR) and not missing at random (NMAR) assumptions of the missing data models. These methods depend only on joint and marginal odds computed from fully and partially observed counts in the tables, respectively. Finally, some real-life datasets are analyzed to illustrate our results, which are confirmed based on simulation studies.     

Model averaging procedure for varying-coefficient partially linear models with missing responses

This paper is concerned with model averaging procedure for varying-coefficient partially linear models with missing responses. The profile least-squares estimation process and inverse probability weighted method are employed to estimate regression coefficients of the partially restricted models, in which the propensity score is estimated by the covariate balancing propensity score method. The estimators of the linear parameters are shown to be asymptotically normal. Then we develop the focused information criterion, formulate the frequentist model averaging estimators and construct the corresponding confidence intervals. Some simulation studies are conducted to examine the finite sample performance of the proposed methods. We find that the covariate balancing propensity score improves the performance of the inverse probability weighted estimator. We also demonstrate the superiority of the proposed model averaging estimators over those of existing strategies in terms of mean squared error and coverage probability. Finally, our approach is further applied to a real data example.     

新中国成立以来中小学教研工作回顾与展望

新中国成立近70年，我国中小学教研工作经历了"初创定型期""停滞偏离期""恢复发展期""改革深化期"和"转型创新期"五个阶段。"教研"是学校教学与教育工作的一种重要实践样态，是我国基础教育工作的重要组成部分，是提升教师专业化水平的重要途径和促进学生全面发展的必要前提。研究发现，我国中小学教研工作存在诸多现实问题，如教师参与教研活动的效果不够明显、教研人员专业发展缺乏制度保障、教研职能定位不准、教研的管理体制不完善等。由此，我们应在"互联网+教育"的新模式下，强化教研与培养学生核心素养相结合；致力于由关注知识传授的研究转向关注全面育人的研究。     

"口味无争辩"?——高低收入阶层膳食健康上的不平等及其分解

我国高低收入阶层间存在着严重的膳食健康上的不平等现象,在讨论其背后的机制时,鲜有文献涉及到口味因素.传统理念认为口味差异天生给定,无需争辩;Becker开创性地认为可以用经济学工具争辩口味问题.通过采用中国家庭追踪调查(CFPS)2010年~2014年三期面板数据进行分析,加入个体固定效应的再中心化影响函数回归,消除了"不可争辩的口味";在此基础.上进行无条件分位数分解,将相同特征条件下系数不同导致的不平等定义为"可争辩的口味"效应.结果显示:在包含收入阶层流动的情况下,"可争辩的口味"和社会经济地位分别可以解释膳食健康不平等的54.3%和44.5%;在不包含收入阶层流动的情况下,二者分别可以解释37.1%和62.3%.人口学特征、个体健康、供给因素的作用很小。结论表明,收入政策只能起到部分作用,政策制定者需要重视对口味的教育引导.这在"健康中国2030"背景下,对于促进全民健康有着重要启示.     

基于EEMD-LSTM的农产品价格短期预测模型研究

本文将集成经验模态分解(EEMD)方法与长短期记忆网络(LSTM)相结合，构建了一个端到端的农产品价格短期预测模型。首先，对原始价格信号进行EEMD分解，得到若干IMF子序列和一个残差序列；然后，运用Fine-to-coarse高低频重构方法对IMF子序列进行高频—低频重构；最后将原始价格序列、高频项、低频项和残差趋势项作为特征，输入到LSTM网络进行训练得到预测模型。本文以广州市江南农副产品市场的富士苹果日价格为例进行实证分析，结果表明，本文提出的EEMD-LSTM模型在农产品价格短期预测问题上具有一定的性能优势。     

Immigrant students and their teachers – exploring various constellations of acculturation orientations and their impact on school adjustment

ABSTRACT

The present study examined what impact various constellations of acculturation orientations of immigrant students and their teachers have on the students’ school adjustment. For this purpose, the study analysed the acculturation orientations of 1106 5th graders and their class teachers in Switzerland. Using multiple regression analysis, we found that immigrant students were more satisfied at school if their teachers had similar attitudes about cultural assimilation and cultural diversity and could, thus, be said to have congruent acculturation orientations. With respect to students’ academic self-concept, immigrant students with a minority orientation whose teachers value cultural diversity including the heritage culture of their students showed a lower academic self-concept despite matching acculturation orientations. We interpret this result as a dilemma of teachers between the endeavour to develop culturally sensitive attitudes and behaviours and the risk to create stereotype threat and its negative effects through addressing cultural differences. Furthermore, a mismatch between the students’ (bi-)national identification at school and the teacher’s perception of the student as an immigrant or a native-born student could be shown to have adverse effects on the academic self-concept in the group of students with older teachers (50+ years).     

Children's humour and the grotesque pleasures in school mealtime socialisation

In this paper, we argue for two propositions: children are socialised and guided to become competent members of school mealtime community, and children have the capacity to modify and challenge existing practices. We draw on Bakhtin's concepts of the carnivalesque laughter and grotesque realism to illustrate how children use humour to test the boundaries of what is permitted. Children's mealtime interactions foster the development of social skills to subvert and negotiate adult authority and manage unfolding interactions between children and adults. We present findings from a child-centred perspective in a primary school in the United Kingdom.     

The 2007 Subprime Market Crisis Through the Lens of European Central Bank Auctions for Short‐Term Funds

We study European banks' demand for short‐term funds (liquidity) during the summer 2007 subprime market crisis. We use bidding data from the European Central Bank's auctions for one‐week loans, their main channel of monetary policy implementation. Our analysis provides a high‐frequency, disaggregated perspective on the 2007 crisis, which was previously studied through comparisons of collateralized and uncollateralized interbank money market rates which do not capture the heterogeneous impact of the crisis on individual banks. Through a model of bidding, we show that banks' bids reflect their cost of obtaining short‐term funds elsewhere (e.g., in the interbank market) as well as a strategic response to other bidders. The strategic response is empirically important: while a naïve interpretation of the raw bidding data may suggest that virtually all banks suffered an increase in the cost of short‐term funding, we find that, for about one third of the banks, the change in bidding behavior was simply a strategic response. We also find considerable heterogeneity in the short‐term funding costs among banks: for over one third of the bidders, funding costs increased by more than 20 basis points, and funding costs vary widely with respect to the country‐of‐origin. The funding costs we estimate using bidding data are also predictive of market‐ and accounting‐based measures of bank performance, reinforcing the usefulness of “revealed preference” information contained in bids.