Regression for non-Euclidean data using distance matrices

Regression methods for common data types such as measured, count and categorical variables are well understood but increasingly statisticians need ways to model relationships between variable types such as shapes, curves, trees, correlation matrices and images that do not fit into the standard framework. Data types that lie in metric spaces but not in vector spaces are difficult to use within the usual regression setting, either as the response and/or a predictor. We represent the information in these variables using distance matrices which requires only the specification of a distance function. A low-dimensional representation of such distance matrices can be obtained using methods such as multidimensional scaling. Once these variables have been represented as scores, an internal model linking the predictors and the responses can be developed using standard methods. We call scoring as the transformation from a new observation to a score, whereas backscoring is a method to represent a score as an observation in the data space. Both methods are essential for prediction and explanation. We illustrate the methodology for shape data, unregistered curve data and correlation matrices using motion capture data from an experiment to study the motion of children with cleft lip.     

俄语引语现象思辨——Л·Петрушевская短篇小说中的引语研究

对Л.Петрушевская短篇小说中新出现的引语现象,运用已有的俄语引语研究成果无力做出解释。中俄学界与欧美学界在引语研究领域有一些概念上的不同认识和理解,通过对其进行必要的分析,并借鉴欧美及国内英语学界在该领域及相关领域的研究成果,可以在一定程度上解决这些新问题。而在此基础上所提出的俄语引语的新体系：直接式引语和间接式引语;语境型引语和功能型引语,能够较为全面地解释Л.Петрушевская及俄罗斯其他后现代作家作品中出现的新的引语现象。     

上海CBD建设及陆家嘴——外滩核心CBD发展构想

CBD是城市的核心和灵魂，也是城市经济功能重要的载体。本文从现代CBD发展的国际趋势入手，对上海城市CBD建设过程的发展状况和存在问题两个方面进行了分析，提出了上海未来CBD的建设思路。在此基础上，对上海陆家嘴一外滩核心CBD区域功能规划进行了深入具体的研究，指出了陆家嘴一外滩核心CBD发展的不足，提出了未来发展的规划目标和功能设想，并在政策和制度上提出了保障措施。     

反垄断执法机关和产业监管机关职能划分的考察维度

我国《反垄断法》对于如何协调反垄断执法机关与产业监管机关之间的职能处于缺位状态,激化了二者在实践中的矛盾。在当前国情下,产业监管机关的存在有其合理性,二者之间实行合作模式有助于调和产业政策与竞争政策的关系。在考察具体职能划分时,需充分结合静态、动态及个别考察维度,既发挥二者各自的优势特点,又结合历史发展的具体阶段以及个案存在,最终实现提高效率的目的。     

An Evaluation of Simulations in Developmental Disabilities (SIDD): Instructional Software that Provides Practice in Behavioral Assessment and Treatment Decisions

ABSTRACT

Simulations in Developmental Disabilities (SIDD) is a multimedia computer program designed to provide undergraduate psychology students with practice in making assessment and treatment decisions. Eighteen undergraduate psychology students participated in an experiment to test the instructional effectiveness of SIDD. Post-test scores were significantly higher in the experimental group who received training with SIDD than in a control group who did not receive training. The students also rated the software positively. Future strategies to further evaluate the software are discussed.     

我国翻译质量评价研究的现状与趋势

翻译质量评价研究在我国译学研究中已经走过了相当一段路程,并取得了不小的成绩。论文围绕我国翻译质量评价之歧路、西方翻译评价理论在中国之引介、翻译质量评价新动向等方面对国内翻译质量评价研究的现状进行梳理,以期对我国的翻译质量评价研究提供参考。作为译学研究的重要组成部分,功能语言学为翻译质量评价提供了强大理论基础,语料库研究为其提供了可资借鉴的实证研究路径,将这二者结合或可使翻译评价研究走出一条新路。     

句法、语义、语用三个平面研究综述

本文介绍了三个平面理论的形成和发展过程,评述了该语法理论存在的价值,提出了一些亟待解决的问题。     

论《经义述闻》的语法观

<经义述闻>因其恢宏博大,不仅完全涵容<经传释词>所表现出的语言学思想--诸如"声近义通"的原则、"因声求义"的方法、"依文作解"的语境观点,而且几乎随处可见到至今仍有重要价值的语言观.王引之天才的语言审析能力和敏锐的语言感受能力,贯穿整部<经义述闻>,从而形成王引之的语言学思想.而王引之的语法观,既反映在<经传释词>对虚词的考释上,又反映在<经义述闻>对句法的推敲上,而通过对<经传释词>和<经义述闻>的比较研究,更便于深入理解王引之语法学思想形成的过程.     

论文学符号的本质与功能性结构关系

符号的本质是在特定结构关系中承担着某种功能并产生着一定意义的媒介物。其最核心的概念是“系统”、“功能”和“意义”。文学符号与语言符号一样 ,也是“能指”和“所指”的统一。在文学符号的内部 ,又包含着各种代码 ,其中最重要的文学代码有“性格代码”、“背景代码”和“情感代码”三种。这就决定着文学符号又是一个具有着强烈的自主功能性、清晰的层次性和内在的编码性的有机运作过程。     

Program Evaluation and Causal Inference With High‐Dimensional Data

In this paper, we provide efficient estimators and honest confidence bands for a variety of treatment effects including local average (LATE) and local quantile treatment effects (LQTE) in data‐rich environments. We can handle very many control variables, endogenous receipt of treatment, heterogeneous treatment effects, and function‐valued outcomes. Our framework covers the special case of exogenous receipt of treatment, either conditional on controls or unconditionally as in randomized control trials. In the latter case, our approach produces efficient estimators and honest bands for (functional) average treatment effects (ATE) and quantile treatment effects (QTE). To make informative inference possible, we assume that key reduced‐form predictive relationships are approximately sparse. This assumption allows the use of regularization and selection methods to estimate those relations, and we provide methods for post‐regularization and post‐selection inference that are uniformly valid (honest) across a wide range of models. We show that a key ingredient enabling honest inference is the use of orthogonal or doubly robust moment conditions in estimating certain reduced‐form functional parameters. We illustrate the use of the proposed methods with an application to estimating the effect of 401(k) eligibility and participation on accumulated assets. The results on program evaluation are obtained as a consequence of more general results on honest inference in a general moment‐condition framework, which arises from structural equation models in econometrics. Here, too, the crucial ingredient is the use of orthogonal moment conditions, which can be constructed from the initial moment conditions. We provide results on honest inference for (function‐valued) parameters within this general framework where any high‐quality, machine learning methods (e.g., boosted trees, deep neural networks, random forest, and their aggregated and hybrid versions) can be used to learn the nonparametric/high‐dimensional components of the model. These include a number of supporting auxiliary results that are of major independent interest: namely, we (1) prove uniform validity of a multiplier bootstrap, (2) offer a uniformly valid functional delta method, and (3) provide results for sparsity‐based estimation of regression functions for function‐valued outcomes.