Likelihood-based cross-validation score for selecting the smoothing parameter in maximum penalized likelihood estimation

Maximum penalized likelihood estimation is applied in non(semi)-para-metric regression problems, and enables us exploratory identification and diagnostics of nonlinear regression relationships. The smoothing parameter A controls trade-off between the smoothness and the goodness-of-fit of a function. The method of cross-validation is used for selecting A, but the generalized cross-validation, which is based on the squared error criterion, shows bad be¬havior in non-normal distribution and can not often select reasonable A. The purpose of this study is to propose a method which gives more suitable A and to evaluate the performance of it.

A method of simple calculation for the delete-one estimates in the likeli¬hood-based cross-validation (LCV) score is described. A score of similar form to the Akaike information criterion (AIC) is also derived. The proposed scores are compared with the ones of standard procedures by using data sets in liter¬atures. Simulations are performed to compare the patterns of selecting A and overall goodness-of-fit and to evaluate the effects of some factors. The LCV-scores by the simple calculation provide good approximation to the exact one if λ is not extremeiy smaii Furthermore the LCV scores by the simple size it possible to select X adaptively They have the effect, of reducing the bias of estimates and provide better performance in the sense of overall goodness-of fit. These scores are useful especially in the case of small sample size and in the case of binary logistic regression.     

Extended BIC for linear regression models with diverging number of relevant features and high or ultra-high feature spaces

In many conventional scientific investigations with high or ultra-high dimensional feature spaces, the relevant features, though sparse, are large in number compared with classical statistical problems, and the magnitude of their effects tapers off. It is reasonable to model the number of relevant features as a diverging sequence when sample size increases. In this paper, we investigate the properties of the extended Bayes information criterion (EBIC) (Chen and Chen, 2008) for feature selection in linear regression models with diverging number of relevant features in high or ultra-high dimensional feature spaces. The selection consistency of the EBIC in this situation is established. The application of EBIC to feature selection is considered in a SCAD cum EBIC procedure. Simulation studies are conducted to demonstrate the performance of the SCAD cum EBIC procedure in finite sample cases.     

The best subset of parameters in min-max linear regression

These Fortran-77 subroutines provide building blocks for Generalized Cross-Validation (GCV) (Craven and Wahba, 1979) calculations in data analysis and data smoothing including ridge regression (Golub, Heath, and Wahba, 1979), thin plate smoothing splines (Wahba and Wendelberger, 1980), deconvolution (Wahba, 1982d), smoothing of generalized linear models (O'sullivan, Yandell and Raynor 1986, Green 1984 and Green and Yandell 1985), and ill-posed problems (Nychka et al., 1984, O'sullivan and Wahba, 1985). We present some of the types of problems for which GCV is a useful method of choosing a smoothing or regularization parameter and we describe the structure of the subroutines.Ridge Regression: A familiar example of a smoothing parameter is the ridge parameter X in the ridge regression problem which we write.     

语音与忠实:罗曼·英伽登的翻译思想探究

罗曼·英伽登是波兰文版《纯粹理性批判》的译者,基于这一翻译经历以及对语言问题的关注,他围绕翻译实践中常见的忠实之难,提出“双层”忠实翻译观。区别于传统的忠实翻译标准,英伽登在语义忠实的基础上,结合文学作品的层次结构,着重强调了语音忠实翻译的必要性和重要性。他对各类“语言—发音”造体,如“节奏质”“乐调”等典型语音形象质进行现象学式的描述分析,视其为影响文学作品“复调和谐”的重要审美相关质,在此基础上探讨语音层在文学作品语言转换中的重要性。他的作品本体论以及语言学思想在其翻译观中得到了更为具体、清晰的展现,英伽登的语音翻译思想为文学作品的跨文化传播、文学和翻译之间的跨学科沟通提供可供参考的“交叉策略”。     

Model averaging for M-estimation

M-estimation is a widely used technique for robust statistical inference. In this paper, we study model selection and model averaging for M-estimation to simultaneously improve the coverage probability of confidence intervals of the parameters of interest and reduce the impact of heavy-tailed errors or outliers in the response. Under general conditions, we develop robust versions of the focused information criterion and a frequentist model average estimator for M-estimation, and we examine their theoretical properties. In addition, we carry out extensive simulation studies as well as two real examples to assess the performance of our new procedure, and find that the proposed method produces satisfactory results.     

Cointegration Detection Using Dynamic Factor Models

A method of information-criterion-based cointegration detection using dynamic factor models is proposed. The results of the data-based and non data-based Monte Carlo simulations suggest that this method is as effective as conventional hypothesis-testing methods. In the proposed method, an observed multivariate time series is described in terms of common stochastic trends plus stationary autoregressive cycles. Then the best model is selected from among alternative models obtained by changing the number of common stochastic trends, on the basis of information criteria. Consequently, the cointegration rank is determined on the basis of the selected model. Two advantages of the proposed method are also discussed.     

超大城市人口—自然资源系统可持续发展水平研究——基于Laplace混合政策模拟

人口增长与集聚为超大城市的发展提供动力,也给其自然资源系统带来极大扰动,使之呈现脆弱性特征;为实现超大城市人口—自然资源可持续发展,近年来政府实施了大量调控政策,但因对城市人口—自然资源系统的复杂互动难以精确量化,导致超大城市人口与自然资源关系治理困难重重。基于此,以北京市为例构建人口—自然资源系统可持续性评价框架,从政策干预视角,分析不同类型调控政策(如人口调控、技术改进、资源管制等)与人口、自然资源的因果关系,并利用Laplace准则结合决策者风险喜好,模拟混合政策干预对人口—自然资源系统可持续性带来的影响。结果显示:政策干预是保证北京市人口—自然资源系统可持续发展的重要手段,其中,人口调控政策是北京市人口—自然资源系统可持续性变动的主要影响因素,资源管制和技术改进是次要影响因素;随着政策干预强度的增加,由于人口系统安全性和自然资源系统脆弱性的互动博弈,北京市人口—自然资源可持续性逐渐趋于稳定;在Laplace情景下,人口安全性减弱了1.82%,损失不大;而自然资源脆弱性减弱了12.13%,收益较高;最终使得人口—自然资源系统可持续性增强了6.23%。因此,对于超大城市的政策干预需...     

儿童文学价值评价问题研究

儿童文学的价值评价讨论儿童文学“应该如何”方面的问题。论文基于新世纪以来我国儿童文学价值建设日益呈现的新情况与新问题,提出儿童文学价值评价问题研究的基本理论视域,澄清当前我国儿童文学价值评价语境及存在的主要问题,并就评价标准建构及延展性的学科发展任务给出思考。     

明代以降六百年间中国的人口流动──评《中国移民史》明清近代分卷

中国移民史）明清近代分卷（第五、第六两卷）围绕战乱、人口损失、移民浪潮这样的线索展开,重点求证本时期移民的数量和规模,描绘出了从明代到近代约六百年间移民分布的总图,可谓完成了一项浩繁的系统工程。但分卷更值得称道的是在学术规范上为读者树立了一个范例：学术是一个批判、继承与积累的过程。背离规范的'研究'并无意义。