Functional principal component analysis for the explorative analysis of multisite–multivariate air pollution time series with long gaps

The knowledge of the urban air quality represents the first step to face air pollution issues. For the last decades many cities can rely on a network of monitoring stations recording concentration values for the main pollutants. This paper focuses on functional principal component analysis (FPCA) to investigate multiple pollutant datasets measured over time at multiple sites within a given urban area. Our purpose is to extend what has been proposed in the literature to data that are multisite and multivariate at the same time. The approach results to be effective to highlight some relevant statistical features of the time series, giving the opportunity to identify significant pollutants and to know the evolution of their variability along time. The paper also deals with missing value issue. As it is known, very long gap sequences can often occur in air quality datasets, due to long time failures not easily solvable or to data coming from a mobile monitoring station. In the considered dataset, large and continuous gaps are imputed by empirical orthogonal function procedure, after denoising raw data by functional data analysis and before performing FPCA, in order to further improve the reconstruction.     

Statistical Certification of Software Systems

Common software release procedures based on statistical techniques try to optimize the trade-off between further testing costs and costs due to remaining errors. We propose new software release procedures where the aim is to certify with a certain confidence level that the software does not contain errors. The underlying model is a discrete time model similar to the geometric Moranda model. The decisions are based on a mix of classical and Bayesian approaches to sequential testing and do not require any assumption on the initial number of errors.     

金融法重构之社会基础:金融利益关系统合化运动

金融利益关系的运动轨迹是金融法重构的基础。通过分析金融利益关系重整、系统性风险、次贷危机三者"前推后"的因果关系脉络,以及"重整"的具体安排、变动过程,推知金融利益关系运动规律与统合化发展趋势。并通过分析"重整"的产生原因,得出金融创新与金融法约束的应然适度关系。基于以上规律、趋势与关系的总结,提出金融法重构的框架思路。     

Breadth of Vocational Interests: The Role of Career Adaptability and Future Orientation

The authors examined the relationship between career adaptability, future orientation, and vocational interests. Specifically, they tested the role of career adaptability and future orientation in promoting a broader range of vocational interests, based on the principle that experiencing more interests can be useful in giving one's best in multiple occupations and in planning a broad range of career goals. A total of 762 Italian adolescents (383 males, 379 females) participated in the study. Results highlight the mediating role of future orientation in the relationship between 4 career adaptability resources and breadth of vocational interests. These results underscore that specific interventions in career adaptability and future orientation may foster a broader range of vocational interests, providing more opportunity for adolescents to respond to the demands of the current job market.     

灾害中残疾人的媒介使用与信息沟通需求——以汶川地震为例

在灾害情况下,残疾人群所面临的沟通困境要远远高于正常人群,甚至连最基本的信息需求都无法得到保障。从2008年汶川地震中残疾人群媒介使用的特征和信息沟通需求来看,对这部分弱势群体的保护需要在法律和政策上给予更多的支持:改善信息发布和传递的渠道,使用新的技术手段,培养残疾人使用媒介的良好习惯。     

浅谈“神似”理论在唐诗英译中的重要作用——以《送友人》的两个英译版本为例

诗歌是一种独特的艺术表现形式,拥有优美的形式和丰富的内容,唐诗也不例外。英译唐诗时,应以再现诗作精神内容风貌为主,即以达到“神似”为翻译第一目标,才能更好地保持唐诗的原貌。本文选择李白《送友人》的两个英译本,分析了“神似”理论在唐诗英译中的重要作用。     

中美大学社团现状与管理模式比较——以河北工程大学与北卡罗来纳州立大学为例

[摘 要]通过对比河北工程大学和北卡州立大学学生社团的发展现状和管理模式,包括学生社团数目、组成及社团的审批、管理、经费、活动、资源等各个方面,对高校学生社团的发展和管理提出了几点建议。     

Embedding latent class regression and latent class distal outcome models into cluster-weighted latent class analysis: a detailed simulation experiment

Usually in latent class (LC) analysis, external predictors are taken to be cluster conditional probability predictors (LC models with external predictors), and/or score conditional probability predictors (LC regression models). In such cases, their distribution is not of interest. Class-specific distribution is of interest in the distal outcome model, when the distribution of the external variables is assumed to depend on LC membership. In this paper, we consider a more general formulation, that embeds both the LC regression and the distal outcome models, as is typically done in cluster-weighted modelling. This allows us to investigate (1) whether the distribution of the external variables differs across classes, (2) whether there are significant direct effects of the external variables on the indicators, by modelling jointly the relationship between the external and the latent variables. We show the advantages of the proposed modelling approach through a set of artificial examples, an extensive simulation study and an empirical application about psychological contracts among employees and employers in Belgium and the Netherlands.     

Adjusted empirical likelihood models with estimating equations for accelerated life tests

This article proposes an adjusted empirical likelihood estimation (AMELE) method to model and analyze accelerated life testing data. This approach flexibly and rigorously incorporates distribution assumptions and regression structures by estimating equations within a semiparametric estimation framework. An efficient method is provided to compute the empirical likelihood estimates, and asymptotic properties are studied. Real-life examples and numerical studies demonstrate the advantage of the proposed methodology.     

Low-pass filter design using locally weighted polynomial regression and discrete prolate spheroidal sequences

The paper concerns the design of nonparametric low-pass filters that have the property of reproducing a polynomial of a given degree. Two approaches are considered. The first is locally weighted polynomial regression (LWPR), which leads to linear filters depending on three parameters: the bandwidth, the order of the fitting polynomial, and the kernel. We find a remarkable linear (hyperbolic) relationship between the cut-off period (frequency) and the bandwidth, conditional on the choices of the order and the kernel, upon which we build the design of a low-pass filter.The second hinges on a generalization of the maximum concentration approach, leading to filters related to discrete prolate spheroidal sequences (DPSS). In particular, we propose a new class of low-pass filters that maximize the concentration over a specified frequency range, subject to polynomial reproducing constraints. The design of generalized DPSS filters depends on three parameters: the bandwidth, the polynomial order, and the concentration frequency. We discuss the properties of the corresponding filters in relation to the LWPR filters, and illustrate their use for the design of low-pass filters by investigating how the three parameters are related to the cut-off frequency.