Distance-based approach in univariate longitudinal data analysis

In this paper, we propose a methodology to analyze longitudinal data through distances between pairs of observations (or individuals) with regard to the explanatory variables used to fit continuous response variables. Restricted maximum-likelihood and generalized least squares are used to estimate the parameters in the model. We applied this new approach to study the effect of gender and exposure on the deviant behavior variable with respect to tolerance for a group of youths studied over a period of 5 years. Were performed simulations where we compared our distance-based method with classic longitudinal analysis with both AR(1) and compound symmetry correlation structures. We compared them under Akaike and Bayesian information criterions, and the relative efficiency of the generalized variance of the errors of each model. We found small gains in the proposed model fit with regard to the classical methodology, particularly in small samples, regardless of variance, correlation, autocorrelation structure and number of time measurements.     

Dynamic inference for non-Markov transition probabilities under random right censoring

The main contribution of this article is the verification of weak convergence of a general non-Markov (NM) state transition probability estimator by Titman, which has not yet been done for any other general NM estimator. A similar theorem is shown for the bootstrap, yielding resampling-based inference methods for statistical functionals. Formulas of the involved covariance functions are presented in detail. Particular applications include the conditional expected length of stay in a specific state, given occupation of another state in the past, and the construction of time-simultaneous confidence bands for the transition probabilities. The expected lengths of stay in a two-sample liver cirrhosis dataset are compared and confidence intervals for their difference are constructed. With borderline significance and in comparison to the placebo group, the treatment group has an elevated expected length of stay in the healthy state given an earlier disease state occupation. In contrast, the Aalen-Johansen (AJ) estimator-based confidence interval, which relies on a Markov assumption, leads to a drastically different conclusion. Also, graphical illustrations of confidence bands for the transition probabilities demonstrate the biasedness of the AJ estimator in this data example. The reliability of these results is assessed in a simulation study.     

国有企业兼并的障碍因素分析

当前我国国有企业兼并受到不少因素的制约, 主要有： 政府在企业兼并中的角色冲突、产权交易市场和中介机构不发达、缺乏有效的长期资金来源、产权关系模糊、法律法规及政策措施不健全、资产评估不规范、地方保护主义严重、企业债务负担沉重、社会保障制度不健全等     

Statistical Inference for Stochastic Dominance and for the Measurement of Poverty and Inequality

We derive the asymptotic sampling distribution of various estimators frequently used to order distributions in terms of poverty, welfare, and inequality. This includes estimators of most of the poverty indices currently in use, as well as estimators of the curves used to infer stochastic dominance of any order. These curves can be used to determine whether poverty, inequality, or social welfare is greater in one distribution than in another for general classes of indices and for ranges of possible poverty lines. We also derive the sampling distribution of the maximal poverty lines up to which we may confidently assert that poverty is greater in one distribution than in another. The sampling distribution of convenient dual estimators for the measurement of poverty is also established. The statistical results are established for deterministic or stochastic poverty lines as well as for paired or independent samples of incomes. Our results are briefly illustrated using data for four countries drawn from the Luxembourg Income Study data bases.     

高校考试制度的改革思路及其制约因素

高校考试制度改革存在着许多制约因素,考试制度改革倡导者与承担者在认识和利益上呈现分离状态。作为人才评价的一种方式,考试制度改革势在必行。树立科学的考试观念,设计多样化的考试形式和考试题型,科学管理试卷,有助于推动高校考试制度的改革。只有这样,才能逐步消除影响考试制度改革的制约因素,实现对人才的科学评价。     

Local Influence Analysis for The Ridge Regression Under Stochastic Linear Restrictions

In this article, we assess the local influence for the ridge regression of linear models with stochastic linear restrictions in the spirit of Cook by using the log-likelihood of the stochastic restricted ridge regression estimator. The diagnostics under the perturbations of constant variance, responses and individual explanatory variables are derived. We also assess the local influence of the stochastic restricted ridge regression estimator under the approach suggested by Billor and Loynes. At the end, a numerical example on the Longley data is given to illustrate the theoretic results.     

The relative efficiency of the restricted estimators in linear regression models

This paper deals with the problem of multicollinearity in a multiple linear regression model with linear equality restrictions. The restricted two parameter estimator which was proposed in case of multicollinearity satisfies the restrictions. The performance of the restricted two parameter estimator over the restricted least squares (RLS) estimator and the ordinary least squares (OLS) estimator is examined under the mean square error (MSE) matrix criterion when the restrictions are correct and not correct. The necessary and sufficient conditions for the restricted ridge regression, restricted Liu and restricted shrunken estimators, which are the special cases of the restricted two parameter estimator, to have a smaller MSE matrix than the RLS and the OLS estimators are derived when the restrictions hold true and do not hold true. Theoretical results are illustrated with numerical examples based on Webster, Gunst and Mason data and Gorman and Toman data. We conduct a final demonstration of the performance of the estimators by running a Monte Carlo simulation which shows that when the variance of the error term and the correlation between the explanatory variables are large, the restricted two parameter estimator performs better than the RLS estimator and the OLS estimator under the configurations examined.     

论对未成年人犯罪适用无期徒刑

阐述了对未成年人犯罪可以适用无期徒刑的观点;提出了对未成年人犯罪适用无期徒刑应当加以严格限制的司法理念,其主要根据是:无期徒刑的严厉性和不经济性、未成年人犯罪主体的身心特点以及顺应保护未成年人权利的国际规范的必然要求,决定了对未成年人犯罪应尽量少用无期徒刑;进一步分析了对未成年人犯罪严格限制适用无期徒刑的司法途径是:首先要严格控制对未成年人犯罪适用无期徒刑的罪质范围,再在此基础上进一步要求对未成年人犯罪适用无期徒刑的罪量达到最高程度.     

谈受限汉语在机器翻译中的运用——以中文简历英译为例

随着国际交流的深入,越来越多的中国人需要把中文简历翻译成英文。但是,简历汉语的特殊性使机器翻译还存有许多不足,导致汉译英的简历表达不尽如人意。要解决这一问题,就有必要对简历中汉语的词汇、句法和语义等进行限制,并建立翻译句模,以简化句子结构,减少或消除汉语表达的歧义,从而提高机器翻译系统的译文质量。受限汉语和句模在机器翻译中的应用,可以推广到饭店订餐和房间预订等受限领域的机器翻译系统中。     

论我国无固定期限劳动合同制度——以用人单位单方解除制度为视角

劳动合同制度是劳动法的核心,劳动合同解除制度是劳动合同制度中的主要内容之一,单方解除则为解除制度的重点.无固定期限劳动合同制度重点在于合同解除后责任承担问题,其法律效力理论体现了对用人单位单方解除权的限制.我国应借鉴国外解雇自由与解雇保护原则相协调的模式,而我国现行立法三种劳动合同适用同一种解除制度,其合理性有待商榷.解除原因认定、解除期限通知等规范的可操作性也应进一步加强.