Powerbuilder中的数据窗口技术

Powerbu ilder是一个优秀的数据库系统开发工具,其核心技术是数据窗口技术,介绍了用Powerbu ilder的数据窗口进行数据库维护、查询、统计、作数据报表的方法,特别是在查询方面,有多种实现数据查询的办法,数据窗口技术显示了Powerbu ilder开发数据库程序的独特魅力。     

遇之自天，泠然希音——司空图《诗品》英译艺术探析

唐代诗人司空图的<诗品>在中国古代诗歌理论史上因影响巨大而占有重要地位,其解读已难,英译更难.王宏印教授推出新的<诗品>英译,通过多种翻译手法的综合运用,实现了自己设定的美学追求.文章从词汇层面、句法层面、译诗的形式、音韵的补救、意美的再现等几个大的方面着手,分析归纳了王宏印教授<诗品>英译的艺术技巧与策略手段.     

土地管理领域中的职务犯罪侦查技能研究

土地管理领域中的职务犯罪案件有其自身的发案特点,侦查工作应在掌握该领域职务犯罪特点的基础上,提升侦查入门、发现线索、侦查切入、侦查取证、侦查深化和侦查把关等6种侦查技能,加大该领域职务犯罪案件的侦查力度。     

英语语篇生成的宏观策略:形式与内容 技术性与艺术性

英语语篇是一个非常泛义的概念,它可以是不同风格或服务于任何目的的英语文本形式。在已有的人们对英语语篇的探讨中,很多研究都是针对语篇的理解而较少注重语篇的生成。英语语篇生成具有英语语篇的形式、内容、技术性和艺术性等四个方面宏观策略。对英语语篇的形式和内容,技术性和艺术性,以及它们之间的关系把握进行探讨对英语语篇文本的生成以及相关的教育领域具有重要的价值和意义。     

跨文化语境中的商标翻译

翻译商标的目的是让目标消费者了解和接受产品。商标的翻译不仅是来源语和目的语之间的语言文字转换．更是一种跨文化交际的过程。从跨文化视角探讨商标翻译,并对商标翻译成功的必要条件、原则和技巧进行探讨。     

基于数字图像处理的纺织物辅助设计模拟系统开发

文章研究并设计了一种基于数字图像处理技术( DIP)的纺织物辅助设计模拟系统。该系统通过将极大化思想、 K-means聚类以及形态学开闭运算有机结合,成功实现了从实际织物组织图中自动提取组织形态学结构,并提出了一种 全新的组织纱线色彩替换算法,将各种组织结构模拟到纺织物设计图样中。实验证明,该系统能够实现很好的组织模拟 效果。     

SEMIPARAMETRIC REGRESSION AND GRAPHICAL MODELS

Semiparametric regression models that use spline basis functions with penalization have graphical model representations. This link is more powerful than previously established mixed model representations of semiparametric regression, as a larger class of models can be accommodated. Complications such as missingness and measurement error are more naturally handled within the graphical model architecture. Directed acyclic graphs, also known as Bayesian networks, play a prominent role. Graphical model-based Bayesian 'inference engines', such as bugs and vibes , facilitate fitting and inference. Underlying these are Markov chain Monte Carlo schemes and recent developments in variational approximation theory and methodology.     

A framework for the comparison of maximum pseudo-likelihood and maximum likelihood estimation of exponential family random graph models

The statistical modeling of social network data is difficult due to the complex dependence structure of the tie variables. Statistical exponential families of distributions provide a flexible way to model such dependence. They enable the statistical characteristics of the network to be encapsulated within an exponential family random graph (ERG) model. For a long time, however, likelihood-based estimation was only feasible for ERG models assuming dyad independence. For more realistic and complex models inference has been based on the pseudo-likelihood. Recent advances in computational methods have made likelihood-based inference practical, and comparison of the different estimators possible.     

Improved estimation methods for unrelated question randomized response techniques

The randomized response technique (RRT) is an important tool, commonly used to avoid biased answers in survey on sensitive issues by preserving the respondents’ privacy. In this paper, we introduce a data collection method for survey on sensitive issues combining both the unrelated-question RRT and the direct question design. The direct questioning method is utilized to obtain responses to a non sensitive question that is related to the innocuous question from the unrelated-question RRT. These responses serve as additional information that can be used to improve the estimation of the prevalence of the sensitive behavior. Furthermore, we propose two new methods for the estimation of the proportion of respondents possessing the sensitive attribute under a missing data setup. More specifically, we develop the weighted estimator and the weighted conditional likelihood estimator. The performances of our estimators are studied numerically and compared with that of an existing one. Both proposed estimators are more efficient than the Greenberg's estimator. We illustrate our methods using real data from a survey study on illegal use of cable TV service in Taiwan.     

Identification-robust moment-based tests for Markov switching in autoregressive models

ABSTRACT

This paper develops tests of the null hypothesis of linearity in the context of autoregressive models with Markov-switching means and variances. These tests are robust to the identification failures that plague conventional likelihood-based inference methods. The approach exploits the moments of normal mixtures implied by the regime-switching process and uses Monte Carlo test techniques to deal with the presence of an autoregressive component in the model specification. The proposed tests have very respectable power in comparison with the optimal tests for Markov-switching parameters of Carrasco et al. (2014 Carrasco, M., Hu, L., Ploberger, W. (2014). Optimal test for Markov switching parameters. Econometrica 82(2):765–784.[Crossref], [Web of Science ®] , [Google Scholar]), and they are also quite attractive owing to their computational simplicity. The new tests are illustrated with an empirical application to an autoregressive model of USA output growth.