浅析英汉文化的语用差异与英语教学中语用能力的培养

英汉文化中的语用差异是跨文化语用学的一个重要研究内容,它对我们的英语教学有着重要的启示和指导意义。本文浅析了英汉文化的主要语用差异和由此导致的语用失误,指出在英语教学中,学生英语交际能力的有效提高要注重跨文化意识和语用能力的培养,努力避免语用失误。     

零级亚纯函数的VB方向

通过计算,证明了一类满足条件:--limr→∞ lnT(r,f)/ln lnr=k (2＜k＜∞)的零级亚纯函数的VB方向的存在性,从而不用充满圆重新证明了这类零级亚纯函数的Borel方向的存在性.     

论唐五代唐诗学与诗歌创作的离合

唐诗学的发展与唐诗创作关系极为密切,但两者并不总是同步。我们视唐五代为唐诗学的萌生期。唐前期的唐诗学与唐诗创作是同步的,即唐诗创作繁荣的同时,唐诗学也由萌生而不断开拓,终于走向自立。唐后期则出现反差,唐诗学全面开拓,唐诗创作则题材转变、萎缩,风格内敛,追求细美幽约,二者大体上呈背离走向。     

论言语交际适应原则的取异策略

适应原则是言语交际的基本原则,取异是遵循适应原则的特殊策略。文章从动因、途径及语用基础三个方面探索了取异策略在言语交际中的具体实施问题。     

Mutual information as a measure of multivariate association: analytical properties and statistical estimation

Mutual information (also known as Kullback–Leibler divergence) can be viewed as a measure of multivariate association in a random vector. The definition incorporates the joint density as well as the marginal densities. We will focus on a representation of mutual information in terms of copula densities that is thus independent of the marginal distributions. This representation yields a different approach to estimating mutual information than the original definition does, as only the copula density has to be estimated. We review analytical properties and examples for selected distributions and discuss methods of nonparametric estimation of copula densities and hence of the mutual information from a sample. Based on a simulation study, we compare the performance of these estimators with respect to bias, standard deviation, and the root mean squared error. The Gauss and the Frank copula are considered as examples.     

Goodness-of-fit tests via ϕ-measures of divergence for censored data

Measures of divergence or discrepancy are used extensively in statistics in various fields. In this article, we are focusing on divergence measures that are based on a class of measures known as Csiszar's divergence measures. In particular, we propose a class of goodness-of-fit tests based on Csiszar's class of measures designed for censored survival or reliability data. Further, we derive the asymptotic distribution of the test statistic under simple and composite null hypotheses as well as under contiguous alternative hypotheses. Simulations are furnished and real data are analysed to show the performance of the proposed tests for different ?-divergence measures.     

环境正义——一种新的正义观

环境正义代表了一种新的正义价值和向度,是一种新型的正义观。其实质是基于人之差异性与同一性相统一的社会正义,它从权利和义务相互对称的角度,强调不同的国家、不同的地区结成的是有差异的共同体。     

Optimal use of historical information

When historical data are available, incorporating them in an optimal way into the current data analysis can improve the quality of statistical inference. In Bayesian analysis, one can achieve this by using quality-adjusted priors of Zellner, or using power priors of Ibrahim and coauthors. These rules are constructed by raising the prior and/or the sample likelihood to some exponent values, which act as measures of compatibility of their quality or proximity of historical data to current data. This paper presents a general, optimum procedure that unifies these rules and is derived by minimizing a Kullback–Leibler divergence under a divergence constraint. We show that the exponent values are directly related to the divergence constraint set by the user and investigate the effect of this choice theoretically and also through sensitivity analysis. We show that this approach yields ‘100% efficient’ information processing rules in the sense of Zellner. Monte Carlo experiments are conducted to investigate the effect of historical and current sample sizes on the optimum rule. Finally, we illustrate these methods by applying them on real data sets.     

Bayesian likelihood robustness in linear models

This paper deals with the problem of robustness of Bayesian regression with respect to the data. We first give a formal definition of Bayesian robustness to data contamination, prove that robustness according to the definition cannot be obtained by using heavy-tailed error distributions in linear regression models and propose a heteroscedastic approach to achieve the desired Bayesian robustness.