A Non-parametric Test for Generalized First-order Autoregressive Models

We derive a non-parametric test for testing the presence of V(X_i,ε_i) in the non-parametric first-order autoregressive model X_i+1=T(X_i)+V(X_i,ε_i)+U(X_i)ε_i+1, where the function T(x) is assumed known. The test is constructed as a functional of a basic process for which we establish a weak invariance principle, under the null hypothesis and under stationarity and mixing assumptions. Bounds for the local and non-local powers are provided under a condition which ensures that the power tends to one as the sample size tends to infinity.The testing procedure can be applied, e.g. to bilinear models, ARCH models, EXPAR models and to some other uncommon models. Our results confirm the robustness of the test constructed in Ngatchou Wandji (1995) and in Diebolt & Ngatchou Wandji (1995).     

论法院依职权调查取证

在审理对象的形成和证据的提出层面实行辩论主义是我国民事司法改革的方向，但是在强调当事人自我责任的同时，也不应忽略法院的作用。如果过分限制法院依职权调查取证的权力，既不利于法院在诉讼中发现真实，也不利于充分保障当事人的程序权利与实体权利，可能造成诉讼能力薄弱者无法实现实体公正。从有利于发现真实、保护当事人合法权益、实现实体公正的角度考虑，有必要适当拓宽我国法院依职权调查取证的范围。     

从功能语言学的视角论《尤利西斯》中语码转换的翻译

爱尔兰著名作家乔伊斯的《尤利西斯》被公认为20世纪最晦涩难懂的英文小说。小说中大量的语码转换是《尤利西斯》的一大特色,也是造成《尤利西斯》晦涩难懂的主要原因之一。本文从韩礼德系统功能语言学的语言功能观入手,不仅探讨了《尤利西斯》中存在的大量的语码转换现象及其诗学价值,而且分析了两个汉译本对原作中的语码转换所采取的不同翻译策略及其功能的再现。     

城市地域结构理论与实践——以广州为例

科学、和谐、宜居城市的形成离不开科学的城市规划理论。在本文中作者首先介绍了几种有代表性的城市地域结构理论,包括同心圆理论、扇形理论、多核心学说等。然后对它们的一一进行了评述,指出了它们的科学性与局限性。进而结合广州城市规划的实践以及广州城市发展过程中所形成的具有一定规模的功能区分析,探讨了这几种主要理论在实践中的指导意义与不足之处,以期能对其他城市的发展提供借鉴,建设更加美满的人类城市生活空间。     

Generalized Sobol sensitivity indices for dependent variables: numerical methods

The hierarchically orthogonal functional decomposition of any measurable function η of a random vector X=(X₁,?…?, X_p) consists in decomposing η(X) into a sum of increasing dimension functions depending only on a subvector of X. Even when X₁,?…?, X_p are assumed to be dependent, this decomposition is unique if the components are hierarchically orthogonal. That is, two of the components are orthogonal whenever all the variables involved in one of the summands are a subset of the variables involved in the other. Setting Y=η(X), this decomposition leads to the definition of generalized sensitivity indices able to quantify the uncertainty of Y due to each dependent input in X [Chastaing G, Gamboa F, Prieur C. Generalized Hoeffding–Sobol decomposition for dependent variables – application to sensitivity analysis. Electron J Statist. 2012;6:2420–2448]. In this paper, a numerical method is developed to identify the component functions of the decomposition using the hierarchical orthogonality property. Furthermore, the asymptotic properties of the components estimation is studied, as well as the numerical estimation of the generalized sensitivity indices of a toy model. Lastly, the method is applied to a model arising from a real-world problem.     

Nonparametric multiple expectile regression via ER-Boost

Expectile regression [Newey W, Powell J. Asymmetric least squares estimation and testing, Econometrica. 1987;55:819–847] is a nice tool for estimating the conditional expectiles of a response variable given a set of covariates. Expectile regression at 50% level is the classical conditional mean regression. In many real applications having multiple expectiles at different levels provides a more complete picture of the conditional distribution of the response variable. Multiple linear expectile regression model has been well studied [Newey W, Powell J. Asymmetric least squares estimation and testing, Econometrica. 1987;55:819–847; Efron B. Regression percentiles using asymmetric squared error loss, Stat Sin. 1991;1(93):125.], but it can be too restrictive for many real applications. In this paper, we derive a regression tree-based gradient boosting estimator for nonparametric multiple expectile regression. The new estimator, referred to as ER-Boost, is implemented in an R package erboost publicly available at http://cran.r-project.org/web/packages/erboost/index.html. We use two homoscedastic/heteroscedastic random-function-generator models in simulation to show the high predictive accuracy of ER-Boost. As an application, we apply ER-Boost to analyse North Carolina County crime data. From the nonparametric expectile regression analysis of this dataset, we draw several interesting conclusions that are consistent with the previous study using the economic model of crime. This real data example also provides a good demonstration of some nice features of ER-Boost, such as its ability to handle different types of covariates and its model interpretation tools.     

Variable selection in partial linear regression with functional covariate

The problem of variable selection is considered in high-dimensional partial linear regression under some model allowing for possibly functional variable. The procedure studied is that of nonconcave-penalized least squares. It is shown the existence of a √n/s_n-consistent estimator for the vector of p_n linear parameters in the model, even when p_n tends to ∞ as the sample size n increases (s_n denotes the number of influential variables). An oracle property is also obtained for the variable selection method, and the nonparametric rate of convergence is stated for the estimator of the nonlinear functional component of the model. Finally, a simulation study illustrates the finite sample size performance of our procedure.     

Penalized contrast estimation in functional linear models with circular data

Our aim is to estimate the unknown slope function in the functional linear model when the response Y is real and the random function X is a second-order stationary and periodic process. We obtain our estimator by minimizing a standard (and very simple) mean-square contrast on linear finite dimensional spaces spanned by trigonometric bases. Our approach provides a penalization procedure which allows to automatically select the adequate dimension, in a non-asymptotic point of view. In fact, we can show that our penalized estimator reaches the optimal (minimax) rate of convergence in the sense of the prediction error. We complete the theoretical results by a simulation study and a real example that illustrates how the procedure works in practice.     

《警察与赞美诗》两个中译本的历时语料对比分析

经典的作品一经译介,往往会有许多重译本.受译作产生年代、所处社会环境及译入语语言发展变化等因素的影响,同一著作的不同译本往往会有所不同.本文以奈达的功能对等理论为基础,对《警察与赞美诗》两个中译本——李文俊和潘明元译本进行比较研究,兼探讨功能对等理论在翻译实践中的应用和意义.本文尝试以这一理论为基础,通过对翻译文本和例句的分析,重点探讨两译本中选词、句式以及风格等方面的差异及在翻译实践中的一些规律,力图从不同的角度丰富翻译理论及实践.     

论给付行政裁量的规制完善

讨论法治思维、法治政府评价的问题,就离不开对行政裁量的考察。考察行政裁量的本质论,就不能绕开对要件裁量说和效果裁量说这种两分法的再认识。探讨自由(便宜)裁量和羁束(法规)裁量的区别问题,不仅有助于把握行政裁量司法统制的界限和基准,而且有助于促进法规范的制定和解释之完善。结合给付行政的增大和裁量权的扩展这种世界性发展趋势,在给付行政领域建构符合该领域特点和规律性的行政责任论,裁量规制和裁量机制本身的完善必不可少。在具有较强裁量性的给付行政领域,宜进行功能性、程序法性的合目的性裁量,而运用和"羁束裁量行为"相对应意义以外的"自由裁量行为"观念,则是不适宜的。在给付行政领域,需要根据每个受给者的具体情形展开具有针对性的、各种各样的灵活应对,这种特点决定了该领域的裁量需要更广阔的空间,同时也需要完善相应的程序和准则,确立基层工作人员状况判断的优位等独具特色的权力运用规则,重视和强调规制手段的活用。