法家思想与秦王朝灭亡关系新论

过去人们对法家思想在秦历史上的作用基本上分为两个阶段,即前期促进了秦的统一,但后期对秦的灭亡也负有不可推卸的责任。不能把秦的灭亡归结于法家思想。秦的灭亡是一个复杂的问题,归结于秦用法家思想统治而导致秦快速灭亡是缺乏根据的。统一后的秦王朝使用法家思想进行统治对于维护当时的统一局面是有积极意义的。历史上使用法家思想进行统治的朝代并不只有秦代,汉以后的政权仍然执行的“外儒内法”的思想,但并没有导致汉王朝很快灭亡。因此应对法家思想进行全面的评价。     

Truncated linear estimation of a bounded multivariate normal mean

We consider the problem of estimating the mean θ$\theta$ of an _Np(θ,_Ip)${\mathrm{N}}_{\mathrm{p}}(\theta ,I_p)$ distribution with squared error loss ∥δ−θ∥²$\parallel \delta -\theta {\parallel }^2$ and under the constraint ∥θ∥≤m$\parallel \theta \parallel \le m$, for some constant m>0$m>0$. Using Stein's identity to obtain unbiased estimates of risk, Karlin's sign change arguments, and conditional risk analysis, we compare the risk performance of truncated linear estimators with that of the maximum likelihood estimator _δmle${\delta }_{\mathrm{mle}}$. We obtain for fixed (m,p)$(m,p)$ sufficient conditions for dominance. An asymptotic framework is developed, where we demonstrate that the truncated linear minimax estimator dominates _δmle${\delta }_{\mathrm{mle}}$, and where we obtain simple and accurate measures of relative improvement in risk. Numerical evaluations illustrate the effectiveness of the asymptotic framework for approximating the risks for moderate or large values of p.     

评《夜色温柔》中男权社会的衰落

《夜色温柔》叙写的是旅居欧洲的美国人迪克.戴弗医生和妻子尼科尔的婚变。10年间他经历过希望、压抑、愧疚、愤怒、失望等多种情感体验,它们在内因和外因的共同作用下,纠结对抗,聚合分裂,本文从性别批评的角度来解读美国小说家菲茨杰拉德的《夜色温柔》,其文本隐喻当时典型的现代西方男权社会中男性中心思想的退位、女权文化崛起。小说通过人物性别意识与叙述视角契合转换的结构方式及男女人物形象塑造的对照谱写了一曲现代男权社会衰落的哀歌。     

论大学生就业指导与思想政治教育的切合点

开展大学生就业指导,是加强和改进高校思想政治教育的有效途径之一,是解决当代大学生成长与发展面临的思想问题和实际问题的重要举措。在实际工作中,将大学生就业指导与思想政治教育相结合,把大学生关注的就业问题作为思想政治教育的切入点,是加强大学生思想政治教育针对性、实效性的重要手段。高校学生思想政治教育工作者应积极探索就业指导与思想政治教育工作紧密结合的切合点,开创高校学生工作的新局面。     

Parental time and working schedules

This paper investigates the effects of working schedules and of other characteristics (including family composition) on the time devoted by mothers and fathers to different activities with children in Canadian households, by using 1992 and 1998 Canadian Time Use Surveys. Switching regression models and models with selection allow us to simultaneously model labour market participation, type of work schedules and allocation of parental time. Working time has a negative and very significant effect on parental time. Hours worked during the day or at night exert a similar effect on parental time, but the impact of hours worked in the evening is by far larger. Time worked in the evening mainly decreases leisure and social activities with children.

An extension of Monte Carlo hypothesis tests

There are many hypothesis testing settings in which one can calculate a “reasonable” test statistic, but in which the null distribution of the statistic is unknown or completely intractable. Fortunately, in many such situations, it is possible to simulate values of the test statistic under the null hypothesis, in which case one can conduct a Monte Carlo test. A difficulty however arises in that Monte Carlo tests, as they are currently structured, are applicable only if ties cannot occur among the values of the test statistics. There is a frequently occurring scenario in which there are lots of ties, namely that in which the null distribution of the test statistic has a (single) point mass. It turns out that one can modify the current form of Monte Carlo tests so as to accommodate such settings. Developing this modification leads to an intriguing identity involving the binomial probability function and its derivatives. In this article, we will briefly explain the modified procedure, discuss simulation studies which demonstrate its efficacy, and provide a proof of the identity referred to above.     

Inference of a hidden spatial tessellation from multivariate data: application to the delineation of homogeneous regions in an agricultural field

Summary.  In a precision farming context, differentiated management decisions regarding fertilization, application of lime and other cultivation activities may require the subdivision of the field into homogeneous regions with respect to the soil variables of main agronomic significance. The paper develops an approach that is aimed at delineating homogeneous regions on the basis of measurements of a categorical and quantitative nature, namely soil type and resistivity measurements at different soil layers. We propose a Bayesian multivariate spatial model and embed it in a Markov chain Monte Carlo inference scheme. Implementation is discussed using real data from a 15-ha field. Although applied to soil data, this model could be relevant in areas of spatial modelling as diverse as epidemiology, ecology or meteorology.     

Mixtures of Linear Regression with Measurement Errors

Existing research on mixtures of regression models are limited to directly observed predictors. The estimation of mixtures of regression for measurement error data imposes challenges for statisticians. For linear regression models with measurement error data, the naive ordinary least squares method, which directly substitutes the observed surrogates for the unobserved error-prone variables, yields an inconsistent estimate for the regression coefficients. The same inconsistency also happens to the naive mixtures of regression estimate, which is based on the traditional maximum likelihood estimator and simply ignores the measurement error. To solve this inconsistency, we propose to use the deconvolution method to estimate the mixture likelihood of the observed surrogates. Then our proposed estimate is found by maximizing the estimated mixture likelihood. In addition, a generalized EM algorithm is also developed to find the estimate. The simulation results demonstrate that the proposed estimation procedures work well and perform much better than the naive estimates.     

On Random and Gibbsian Particle Motions for Point Processes Evolving in Space and Time

This article presents an analysis of space-time interdependencies of spatial point processes considering random and deterministic Gibbsian point motions caused by repulsion effects between particles. Two deterministic models of Gibbsian motions are considered by formulating a constant (i.e., Strauss-like) and a linear interaction motion functions. Given that theoretical development of continuous space-time stochastic processes are mathematically intractable, we have mainly based our analysis on numerical simulations. Our results suggest that to fully understand such complex dynamics, the analysis of purely spatial patterns should be combined with their interactions in the space-time domain. Otherwise, analysis of pure spacial patterns may not fully explain the real mechanism generating such dynamical configurations. We highlight that adding movement to sedentary points opens new areas of application and research to study biological phenomena, where particles not only evolve through time but also can change spatial positions in terms of their neighbor locations.     

Econometric disequilibrium models

Four basic strands in the disequilibrium literature are identified. Some examples are discussed and the canonical econometric disequilibrium model and its estimation are dealt with in detail. Specific criticisms of the canonical model,dealing with price and wage rigidity, with the nature of the min condition and the price-adjustment equation, are considered and a variety of modifications is entertained. Tests of the “equilibrium vs. disequilibrium” hypothesis are discussed, as well as several classes of models that may switch between equilibrium and disequilibrium modes. Finally, consideration is given to multimarket disequilibrium models with particular emphasis on the problems of coherence and estimation.