论业余篮球队核心队员的能力与培养

运动员要想提高篮球运动技术水平,并在校际比赛中取得胜利,不仅要具备扎实过硬的基本功和必胜的信念,而且更重要的是球队要有一名能力较强的核心队员。为了培养核心队员的能力,应加强对其篮球意识的培养传授、基本功训练、身体素质和心理素质训练。只有具备了良好的身体素质、心理素质、全面熟练的基本功和基本技术,才能在比赛中展示自己的能力,取得比赛的胜利。     

新形势下高校实验人员队伍的建设探讨

把高校实验室仅仅理解成高校教学育人的辅助设施是错误的。提高实验室的整体水平,单靠大量精密贵重的仪器设备远远不够,还要建立一支稳定的、高素质的专业技术队伍。文章分析了高素质实验队伍应具备的条件和培养手段,并指出了建设高水平实验队伍的对策建议。     

Bayesian analysis of panel data using an MTAR model

Bayesian analysis of panel data using a class of momentum threshold autoregressive (MTAR) models is considered. Posterior estimation of parameters of the MTAR models is done by using a simple Markov Chain Monte Carlo (MCMC) algorithm. Selection of appropriate differenced variables, test for asymmetry and unit roots are recast as model selections and a simple way of computing posterior probabilities of the candidate models is proposed. The proposed method is applied to the yearly unemployment rates of 51 US states and the results show strong evidence of stationarity and asymmetry.     

高校学报编辑选稿行为的影响因素探析

编辑选择稿件的过程是一个复杂的思维过程,不可避免地受到编辑自身因素(学识水平、学科方向、性格弱点)和外在因素(办刊宗旨、专家审稿、权情关系、信息反馈)的影响和制约。     

CORRECTING FOR KURTOSIS IN DENSITY ESTIMATION

Using a global window width kernel estimator to estimate an approximately symmetric probability density with high kurtosis usually leads to poor estimation because good estimation of the peak of the distribution leads to unsatisfactory estimation of the tails and vice versa. The technique proposed corrects for kurtosis via a transformation of the data before using a global window width kernel estimator. The transformation depends on a “generalised smoothing parameter” consisting of two real-valued parameters and a window width parameter which can be selected either by a simple graphical method or, for a completely data-driven implementation, by minimising an estimate of mean integrated squared error. Examples of real and simulated data demonstrate the effectiveness of this approach, which appears suitable for a wide range of symmetric, unimodal densities. Its performance is similar to ordinary kernel estimation in situations where the latter is effective, e.g. Gaussian densities. For densities like the Cauchy where ordinary kernel estimation is not satisfactory, our methodology offers a substantial improvement.     

Applying classification algorithms in practice

In this paper we present a perspective on the overall process of developing classifiers for real-world classification problems. Specifically, we identify, categorize and discuss the various problem-specific factors that influence the development process. Illustrative examples are provided to demonstrate the iterative nature of the process of applying classification algorithms in practice. In addition, we present a case study of a large scale classification application using the process framework described, providing an end-to-end example of the iterative nature of the application process. The paper concludes that the process of developing classification applications for operational use involves many factors not normally considered in the typical discussion of classification models and algorithms.     

Detecting Overdispersion in Large Scale Surveys: Application to a Study of Education and Social Class in Britain (with Comments)

A practical problem with large scale survey data is the potential for overdispersion. Overdispersion occurs when the data display more variability than is predicted by the variance–mean relationship for the assumed sampling model. This paper describes a simple strategy for detecting and adjusting for overdispersion in large scale survey data. The method is primarily motivated by data on the relationship between social class and educational attainment obtained from a 2% sample from the 1991 census of the population of Great Britain. Overdispersion can be detected by first grouping the data into a number of strata of approximately equal size. Under the assumption that the observations are independent and there is no variability in the parameter of interest, there is a direct relationship between the nominal standard errors and the empirical or sample standard deviation of the parameter estimates obtained from each of the separate strata. With the 2% sample from the British census data, quite a discernible departure from this relationship was found, indicating overdispersion. After allowing for overdispersion, improved and more realistic measures of precision of the strength of the social class–education associations were obtained.     

基于博弈分析的农村信用社产权改革路径选择

随着我国农村信用社改革的步步深化,新型产权组织模式与运行机制的构建已经走到了攻坚阶段。文章在归纳分析农村信用社改革与发展背景及基本现状的基础上,围绕政府与农村信用社双方的益损值,对政府推行农村信用社合作制规范进行了博弈分析,由最终的纳什均衡分析结果,得出了在现有农村信用社基础上搞统一的合作制规范不切实际,农村信用社改革必须走“多元化”产权组织模式道路的结论,并就新时期如何进一步发展与完善农村信用社“多元化”产权组织模式提出了几点政策性建议。     

Best subset selection of autoregressive models with exogenous variables and generalized autoregressive conditional heteroscedasticity errors

Summary.  We develop an efficient way to select the best subset autoregressive model with exogenous variables and generalized autoregressive conditional heteroscedasticity errors. One main feature of our method is to select important autoregressive and exogenous variables, and at the same time to estimate the unknown parameters. The method proposed uses the stochastic search idea. By adopting Markov chain Monte Carlo techniques, we can identify the best subset model from a large of number of possible choices. A simulation experiment shows that the method is very effective. Misspecification in the mean equation can also be detected by our model selection method. In the application to the stock-market data of seven countries, the lagged 1 US return is found to have a strong influence on the other stock-market returns.     

Variations in Child Care by Grandparents During the First Three Years

Routine child care by grandparents was examined for 1,229 children who were participants in the National Institute of Child Health and Human Development (NICHD) Study of Early Child Care. Four groups were identified: extended full‐time care, extended part‐time care, sporadic care, and no routine care during the first three years. The odds of sporadic child care by grandparents were higher when mothers were relatively young and worked nonstandard hours. The odds of extended full‐time grandparent care versus extended part‐time grandparent care were higher for mothers of color and mothers with more extensive full‐time employment. All types of grandparent care were more likely when a grandparent lived in the household. These findings suggest that grandparent care is heterogeneous and may occur in response to different family circumstances.