基于fused惩罚的稀疏主成分分析

本文旨在研究基于fused惩罚的稀疏主成分分析方法，以适用于相邻变量之间高度相关甚至完全相等的数据情形。首先，从回归分析角度出发，提出一种求解稀疏主成分的简便思路，给出一种广义的稀疏主成分模型—— GSPCA模型及其求解算法，并证明在惩罚函数取1-范数时，该模型与现有的稀疏主成分模型——SPC模型的求解结果一致。其次，本文提出将fused惩罚与主成分分析相结合，得到一种fused稀疏主成分分析方法，并从惩罚性矩阵分解和回归分析两个角度，给出两种模型形式。在理论上证明了两种模型的求解结果是一致的，故将其统称为FSPCA模型。模拟实验显示，FSPCA模型在处理相邻变量之间高度相关甚至完全相等的数据集上的表现良好。最后，将FSPCA模型应用于手写数字识别，发现与SPC模型相比，FSPCA模型所提取的主成分具备更好的解释性，这使得该模型更具实用价值。     

Control Chart for Monitoring Autocorrelated Process with Multiple Exogenous Inputs

We propose to use AR-Sieve Bootstrap in the construction of a control chart of an autocorrelated process influenced by multiple exogenous inputs. The control charts are compared with Exponentially Weighted Moving Average (EWMA) control chart through a simulation study. AR-Sieve bootstrap control limits are narrower than EWMA control limits. While the proposed method yields a higher rate of false alarms, it is quick in detecting even minimal structural changes.     

空气污染治理与公众健康———来自“大气十条”政策的证据

为探究《大气污染防治行动计划》 (以下简称“大气十条”)的健康效应,本文基于中国健康与营养调查(CHNS)数据及省级面板数据,利用基于多项Logit模型的双重差分法(Logit-DID),从微观与宏观两个维度考察“大气十条”政策的健康改善效应及其传导机制,并进一步通过异质性分析探讨环境健康不平等的内在原因 研究发现:“大气十条”实施带来显著的健康效应,该政策不仅能有效控制与空气污染高度相关疾病的发病率和死亡占比,还能够间接降低受空气污染影响较小的疾病病情。其作用机理主要通过控制PM2.5浓度改善公众健康,同时该政策对二氧化硫(SO2)、氮氧化物、烟(粉)尘等其 他污染物浓度的下降起到了协同作用。进一步分析显示环境福利不公平的现象依然存在,“大气十条”政 策显著降低了疾病高发人群的发病率,且对女性、城镇居民和低、高年龄段等疾病高发人群的健康影响更显著。本文为政府构建环境健康公平发展路径,推进“健康中国”战略提供了经验证据和政策借鉴。     

Sparse group lasso for multiclass functional logistic regression models

Sparsity-inducing penalties are useful tools for variable selection and are also effective for regression problems where the data are functions. We consider the problem of selecting not only variables but also decision boundaries in multiclass logistic regression models for functional data, using sparse regularization. The parameters of the functional logistic regression model are estimated in the framework of the penalized likelihood method with the sparse group lasso-type penalty, and then tuning parameters for the model are selected using the model selection criterion. The effectiveness of the proposed method is investigated through simulation studies and the analysis of a gene expression data set.     

An m-estimation-based model selection criterion with a data-oriented penalty

In Wu and Zen (1999), a linear model selection procedure based on M-estimation is proposed, which includes many classical model selection criteria as its special cases, and it is shown that the selection procedure is strongly consistent for a variety of penalty functions. In this paper, we will investigate its small sample performances for some choices of fixed penalty functions. It can be seen that the performance varies with the choice of the penalty. Hence, a randomized penalty based on observed data is proposed, which preserves the consistency property and provides improved performance over a fixed choice of penalty functions.     

A permutation alternative and other test procedures for spatially correlated data in one-way anova

Research in many disciplines involves data with spatially correlated observations. Spatial dependence violates the independent errors assumption required for techniques such as the standard one-way analysis of variance for a completely randomized design. The testing methodology within the correlated errors approach has not been investigated within a spatial context. For one-way fixed effects analysis of variance, a permutation test and tests associated with the correlated errors approach are investigated through simulation. No single test was superior with respect to both power and size but the standard Wald F test and a simple adjustment to it performed well overall.     

1906-1908年的郑孝胥与预备立宪公会

考虑到我国未来年度的OD分布预测中的路网构成变化、区域经济布局变动、区域经济增长速度差异等一些具有时变性和特殊性因素，采用在“四阶段法”运量预测基础上改进而成的“三阶段法”进行高速铁路短期客运量预测。首先采用组合预测模型进行趋势运量预测，然后采用多元LOGIT模型进行方式分担，最后采用弹性系数诱增模型进行诱增运量预测。以京沪高铁为例，采用“三阶段法”预测了2014年和2015年京沪高铁本线及跨线单向客流量。     

Influence of National Qualifications Frameworks in Conceptualising Feedback to Students

Social work students in Britain receive feedback on a range of academic and practice issues as they progress through qualifying courses, however the way in which feedback differs to reflect the increasing complexity of learning as the course progresses is unclear. There is little, if any, guidance at a national level and the most widely known documents that provide information about the hierarchy of qualifications are the National Qualifications Frameworks (NQFs). Despite the widespread acceptance of NQFs there is little evidence supporting their use in professional areas such as social work. This study uses a documentary analysis to critique the Scottish Credit and Qualifications Framework (SCQF). The findings suggest that there are fundamental difficulties with the SCQF and its value in helping academics to better conceptualise feedback that reflects the increasing complexity of learning throughout the social work qualifying course. Whilst the SCQF is specific to a Scottish context, it is suggested that the inherent limitations and dominance of a neo-liberal ideology are common to other NQFs. It may be necessary to create the conditions where academics and students are able to discuss and debate the merits of NQFs and their implementation in social work qualifying courses.     

Deriving Behavior Model Parameters from Survey Data: Self‐Protective Behavior Adoption During the 2009–2010 Influenza A(H1N1) Pandemic

In this paper, we demonstrate how public opinion surveys can be designed to collect information pertinent to computational behavior modeling, and we present the results of a public opinion and behavior survey conducted during the 2009–2010 H1N1 influenza pandemic. The results are used to parameterize the Health Belief Model of individual health‐protective decision making. Survey subjects were asked questions about their perceptions of the then‐circulating influenza and attitudes towards two personal protective behaviors: vaccination and avoidance of crowds. We empirically address two important issues in applying the Health Belief Model of behavior to computational infectious disease simulation: (1) the factors dynamically influencing the states of the Health Belief Model variables and (2) the appropriateness of the Health Belief Model in describing self‐protective behavior in the context of pandemic influenza.     

Blood on the tracks: Critically re‐reading a government occupational health and safety inquiry

This paper brings to light forms of interpretive closure embedded in a Government inquiry into rail industry occupational safety and heath. The paper shows how particular interpretive moves by the Inquiry had the effect of obscuring a critical analysis of economic and political relations. The analysis uses publicly available documentary data and is undertaken using interpretive and political economic forms of analysis in a multiple framework approach.