中介语与中国式英语

大学教师应当利用中介语理论指导大学外语教学 ,分析语言的“石化”产生的原因 (负偏移的影响、母语的干扰、对中介语错误的忽略、等等 )。应在教学中注意正确的语言导向和语言教学法 ,认真对待学生在外语学习与习得过程中的中介语错误 ,把它当作语言教学的有利契机 ,在最大程度上纠正学生的中国式英语 ,帮助他们培养正确的语感 ,促使大学外语的课堂教学保质保量地得以进行。     

“烘云托月”与“说不可说”冯友兰新理学“负方法”的关学阐释

在冯友兰新理学关于方法论的论述中,其用“负方法”对形而上学的“讲述”对美学有着深刻的启示意义,甚至可以说它本身就涵蕴着丰富的关学意味。道家的方法、禅宗的方法和诗的言说,是“负方法”的三种典型言说方式,这三种言说形式具有美学阐释的可能性,表现在直觉性、神秘性、超越性和浑整性4个方面。     

社会转型中的正当防卫界限

我国正当防卫制度在犯罪论体系中逻辑错位、在司法实践中缺位与越位的现象凸显。其诸多弊端的根源在于漠视本土文化传统和社会转型的实践。重构现行正当防卫界限,从法益衡量说走向社会相当性说,从正面要件界定走向负面清单甄选,有利于保障人权,实现防卫善治。     

英语否定词在语言表达中的应用

否定词的用法对学习英语的学生来说一直是个难题。因为在英语中否定词的用法和意义是灵活多变的。本文主要从四个方面阐述了英语否定词在语言表达中的具体应用。旨在帮助学生更有效 ,灵活地理解和使用。     

“是……的”句型日译汉的偏误分析

据实际语料考察,日本留学生在日译汉过程中使用“是……的”句型的出错率较高。留学生误译语句中有的没有使用“是……的”句型,有的虽然使用了“是……的”句型,但语序等方面存在问题。在分析偏误产生的原因的基础上,通过朗读等语感训练方式,可以提高“是……的”句型使用的正确率。     

The exponential distribution analog of the Grubbs–Weaver method

Abstract

Grubbs and Weaver (1947 Grubbs, F. E., and C. L. Weaver. 1947. The best unbiased estimate of population standard deviation based on group ranges. Journal of the American Statistical Association 42 (238):224–41. doi: 10.2307/2280652.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) suggest a minimum-variance unbiased estimator for the population standard deviation of a normal random variable, where a random sample is drawn and a weighted sum of the ranges of subsamples is calculated. The optimal choice involves using as many subsamples of size eight as possible. They verified their results numerically for samples of size up to 100, and conjectured that their “rule of eights” is valid for all sample sizes. Here we examine the analogous problem where the underlying distribution is exponential and find that a “rule of fours” yields optimality and prove the result rigorously.     

Comparison of Interval Estimators of Pr(X < Y) in the Two-parameter Exponential Distribution

We consider confidence intervals for the stress–strength reliability Pr(X< Y) in the two-parameter exponential distribution. We have derived the Bayesian highest posterior density interval using non-informative prior distributions. We have compared its performance with the intervals based on the generalized pivot variable intervals in terms of their coverage probabilities and expected lengths. Our simulation study shows that the Bayesian interval performs better according to the criteria used, especially when the sample sizes are very small. An example is given.     

Accurate estimation for extra-Poisson variability assuming random effect models

In this study, the components of extra-Poisson variability are estimated assuming random effect models under a Bayesian approach. A standard existing methodology to estimate extra-Poisson variability assumes a negative binomial distribution. The obtained results show that using the proposed random effect model it is possible to get more accurate estimates for the extra-Poisson variability components when compared to the use of a negative binomial distribution where it is possible to estimate only one component of extra-Poisson variability. Some illustrative examples are introduced considering real data sets.     

A new regression model for bimodal data and applications in agriculture

We define the odd log-logistic exponential Gaussian regression with two systematic components, which extends the heteroscedastic Gaussian regression and it is suitable for bimodal data quite common in the agriculture area. We estimate the parameters by the method of maximum likelihood. Some simulations indicate that the maximum-likelihood estimators are accurate. The model assumptions are checked through case deletion and quantile residuals. The usefulness of the new regression model is illustrated by means of three real data sets in different areas of agriculture, where the data present bimodality.     

Zero-inflated sum of Conway-Maxwell-Poissons (ZISCMP) regression

While excess zeros are often thought to cause data over-dispersion (i.e. when the variance exceeds the mean), this implication is not absolute. One should instead consider a flexible class of distributions that can address data dispersion along with excess zeros. This work develops a zero-inflated sum-of-Conway-Maxwell-Poissons (ZISCMP) regression as a flexible analysis tool to model count data that express significant data dispersion and contain excess zeros. This class of models contains several special case zero-inflated regressions, including zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB), zero-inflated binomial (ZIB), and the zero-inflated Conway-Maxwell-Poisson (ZICMP). Through simulated and real data examples, we demonstrate class flexibility and usefulness. We further utilize it to analyze shark species data from Australia's Great Barrier Reef to assess the environmental impact of human action on the number of various species of sharks.