描述译学的语言学模式

始于20世纪70年代的描述翻译学,因其具有理论和应用双重属性,有助于翻译理论研究和实践研究之间的沟通.而系统功能语言学,作为一种基于人类学、社会学、符号学的现代语言学理论,与描述翻译学具有相通的语言观、系统观和功能观.由此,系统功能语言学的系统理论、功能理论、语境理论,能够为描述翻译学提供一种更为细致、有效的研究途径.     

高校社团对基层团组织的功能替代

在新时期里,高校基层团组织的传统工作模式受到了前所未有的挑战,其功能也呈现出明显弱化的迹象;而学生社团则在高校中蓬勃发展,甚至对团组织起到了某种程度上的“功能替代”作用。一种功能互补的趋势正在悄然形成中。     

Transformed generalized linear models

The estimation of data transformation is very useful to yield response variables satisfying closely a normal linear model. Generalized linear models enable the fitting of models to a wide range of data types. These models are based on exponential dispersion models. We propose a new class of transformed generalized linear models to extend the Box and Cox models and the generalized linear models. We use the generalized linear model framework to fit these models and discuss maximum likelihood estimation and inference. We give a simple formula to estimate the parameter that index the transformation of the response variable for a subclass of models. We also give a simple formula to estimate the r$r$th moment of the original dependent variable. We explore the possibility of using these models to time series data to extend the generalized autoregressive moving average models discussed by Benjamin et al. [Generalized autoregressive moving average models. J. Amer. Statist. Assoc. 98, 214–223]. The usefulness of these models is illustrated in a simulation study and in applications to three real data sets.     

功能语篇分析在高职大学英语阅读教学中的运用

本文认为功能语篇衔接理论的运用,有助于提高教学质量和学习成效。     

论电子商务法基本原则

电子商务法学界对电子商务法基本原则的认识仍存在种种分歧和不足.技术中立原则只是民法平等原则的细化,不能成为电子商务法基本原则.在梳理国内现有理论研究并汲取合理成分的基础上,以法律基本原则的原理为基础,从电子商务法解决的核心问题是在非面对面交易环境中,如何确保当事人能够获得商品和价款出发,提出电子商务法基本原则是安全原则.功能等同是判定利用新型信息技术所实施的法律行为有效与否的标准,是安全原则的重要外延和具体化.安全原则要求第三方电子商务平台针对平台内发生的第三方侵权行为负有合理的注意义务.在安全原则指引下,技术中立非绝对,应包含国家安全等例外规则.     

应用同伦正则化算法反演二维溶质运移模型中的弥散系数

利用同伦正则化算法探讨了二维对流弥散方程的依赖空间变量的弥散系数反演问题.讨论了初始迭代值、数值微分步长、以及收敛精度对算法实现的影响.数值模拟表明,同伦正则化算法对于此类参数反演问题是一种有效的方法.     

On the computation of the noncentral <Emphasis Type="Italic">F</Emphasis> and noncentral beta distribution

Unfortunately many of the numerous algorithms for computing the comulative distribution function (cdf) and noncentrality parameter of the noncentral F and beta distributions can produce completely incorrect results as demonstrated in the paper by examples. Existing algorithms are scrutinized and those parts that involve numerical difficulties are identified. As a result, a pseudo code is presented in which all the known numerical problems are resolved. This pseudo code can be easily implemented in programming language C or FORTRAN without understanding the complicated mathematical background. Symbolic evaluation of a finite and closed formula is proposed to compute exact cdf values. This approach makes it possible to check quickly and reliably the values returned by professional statistical packages over an extraordinarily wide parameter range without any programming knowledge. This research was motivated by the fact that a very useful table for calculating the size of detectable effects for ANOVA tables contains suspect values in the region of large noncentrality parameter values compared to the values obtained by Patnaik’s 2-moment central-F approximation. The cause is identified and the corrected form of the table for ANOVA purposes is given. The accuracy of the approximations to the noncentral-F distribution is also discussed. The authors wish to thank Mr. Richárd Király for his preliminary work. The authors are grateful to the Editor and Associate Editor of STCO and the unknown reviewers for their helpful suggestions.     

The Bayes rule of the variance parameter of the hierarchical normal and inverse gamma model under Stein's loss

For the variance parameter of the hierarchical normal and inverse gamma model, we analytically calculate the Bayes rule (estimator) with respect to a prior distribution IG (alpha, beta) under Stein's loss function. This estimator minimizes the posterior expected Stein's loss (PESL). We also analytically calculate the Bayes rule and the PESL under the squared error loss. Finally, the numerical simulations exemplify that the PESLs depend only on alpha and the number of observations. The Bayes rules and PESLs under Stein's loss are unanimously smaller than those under the squared error loss.     

An Adaptive Functional Autoregressive Forecast Model to Predict Electricity Price Curves

We propose an adaptive functional autoregressive (AFAR) forecast model to predict electricity price curves. With time-varying operators, the AFAR model can be safely used in both stationary and nonstationary situations. A closed-form maximum likelihood (ML) estimator is derived under stationarity. The result is further extended for nonstationarity, where the time-dependent operators are adaptively estimated under local homogeneity. We provide theoretical results of the ML estimator and the adaptive estimator. Simulation study illustrates nice finite sample performance of the AFAR modeling. The AFAR model also exhibits a superior accuracy in the forecast exercise of the California electricity daily price curves compared to several alternatives.     

Uniform in bandwidth consistency for various kernel estimators involving functional data

The paper investigates various nonparametric models including regression, conditional distribution, conditional density and conditional hazard function, when the covariates are infinite dimensional. The main contribution is to prove uniform in bandwidth asymptotic results for kernel estimators of these functional operators. Then, the application issues, involving data-driven bandwidth selection, are discussed.