Lightning detection in British Columbia: An example of using system operation at unknown reliability to estimate component reliability

Lightning data collected over three dry seasons from the detection system operated by the British Columbia Ministry of Forests were analyzed to estimate the distribution of lightning signal strength and component detection efficiencies. The analysis was based on more than 165,000 lightning-strike records, where component detectors served both as lightning finders and as data collectors for evaluating the performance of other component detectors in the network. In spite of the unusual feature of this application involving a system evaluating itself, much was revealed to identify weaknesses and suggest improvements. A postanalysis system-modification update is included.     

Alternative transformations to eliminate fixed effects

In a panel data model with fixed individual effects, a number of alternative transformations are available to eliminate these effects such that the slope parameters can be estimated from ordinary least squares on transformed data. In this note we show that each transformation leads to algebraically the same estimator if the transformed data are used efficiently (i.e. if GLS is applied). If OLS is used, however, differences may occur and the routinely computed variances, even after degrees of freedom correction, are incorrect. In addition, it may matter whether “redundant” observations are used or not.     

控制权转移与企业业绩

本文利用1997-2001年发生控制权转移的企业为样本,运用因子分析方法,研究了控制权转移与企业业绩之间的关系,创新性地对企业业绩从盈利性和增长性两方面进行分解评价,并进一步辨识了并购行为的特征。研究结论:(1)与市场整体水平相比,控制权转移企业中业绩较好的企业占27%,业绩较差的占22%,业绩中等的占51%;(2)控制权转移虽然能短暂地提升业绩,但并不能长久提升;业绩短暂提升是通过业绩增长实现的,而企业盈利能力始终没有提升;(3)控制权转移的财务性并购特征高于战略性并购特征。     

双重视角下的中国经济周期混频测度

本文同时在混频动态因子模型截距和方差项引入马尔科夫区制转换过程,从经济增长速度和波动强度的双重角度对我国经济周期不同阶段间的运行特征进行详细考察。研究表明,我国经济周期呈现出明显不同的阶段性特征;不同状态间的转移概率存在非对称性;新常态背景下经济运行继续保持微波化的平稳运行态势是大概率事件。此外,本文提取的一致景气指数与我国实际季度GDP增长率的走势基本一致,能较为准确地反映各个时期的经济形势。     

A methodology for quantifying the effect of missing data on decision quality in classification problems

Decision making is often supported by decision models. This study suggests that the negative impact of poor data quality (DQ) on decision making is often mediated by biased model estimation. To highlight this perspective, we develop an analytical framework that links three quality levels – data, model, and decision. The general framework is first developed at a high-level, and then extended further toward understanding the effect of incomplete datasets on Linear Discriminant Analysis (LDA) classifiers. The interplay between the three quality levels is evaluated analytically – initially for a one-dimensional case, and then for multiple dimensions. The impact is then further analyzed through several simulative experiments with artificial and real-world datasets. The experiment results support the analytical development and reveal nearly-exponential decline in the decision error as the completeness level increases. To conclude, we discuss the framework and the empirical findings, elaborate on the implications of our model on the data quality management, and the use of data for decision-models estimation.     

城市群经济网络与经济增长——基于大数据与网络分析方法的研究

借助大数据时代下获得的海量数据,本文分析了长三角城市群的经济网络特征,重点研究了城市群经济网络的增长效应。首先,构建了长三角城市群的人口流动网络、企业组织网络与电子商务网络,对其各自的网络结构特征进行了对比。其次,将网络分析方法与空间计量模型结合起来,使用扩展的J检验方法对不同网络结构下的模型设定方法进行了识别,考察了经济网络带来的溢出效应对于城市群经济增长的影响。分析结果显示,三种经济网络下长三角城市群均呈现出了“中心-外围”的网络结构,其中上海、杭州、苏州、南京及无锡位于城市群经济网络的核心圈层。对网络结构的模型识别结果显示,中心城市在长三角城市群经济网络的溢出效应中扮演着重要角色。具体而言,在人口流动网络下,资本、政府行为存在显著为负的网络溢出效应;在企业组织网络下,人口规模、对外开放呈现出显著为正的网络溢出效应;在电子商务网络下,政府行为存在显著为负的网络溢出效应,对外开放呈现出显著为正的网络溢出效应。     

A New Lens on High School Dropout: Use of Correspondence Analysis and the Statewide Longitudinal Data System

The combination of log-linear models and correspondence analysis have long been used to decompose contingency tables and aid in their interpretation. Until now, this approach has not been applied to the education Statewide Longitudinal Data System (SLDS), which contains administrative school data at the student level. While some research has been conducted using the SLDS, its primary use is for state education administrative reporting. This article uses the combination of log-linear models and correspondence analysis to gain insight into high school dropouts in two discrete regions in Kentucky, Appalachia and non-Appalachia, defined by the American Community Survey. The individual student records from the SLDS were categorized into one of the two regions and a log-linear model was used to identify the interactions between the demographic characteristics and the dropout categories, push-out and pull-out. Correspondence analysis was then used to visualize the interactions with the expanded push-out categories, boredom, course selection, expulsion, failing grade, teacher conflict, and pull-out categories, employment, family problems, illness, marriage, and pregnancy to provide insights into the regional differences. In this article, we demonstrate that correspondence analysis can extend the insights gained from SDLS data and provide new perspectives on dropouts. Supplementary materials for this article are available online.     

Breaking Carbon Lock-In: Path Dependencies in Large-Scale Transportation Infrastructure Projects

The central focus of this paper is to highlight the ways in which path dependencies and increasing returns (network effects) serve to reinforce carbon lock-in in large-scale road transportation infrastructure projects. Breaking carbon lock-in requires drastic changes in the way we plan future transportation infrastructure projects, and documentary evidence presented here from the metropolitan regions of Copenhagen, Denmark and Portland, USA, indicate that there may be a discontinuity in the system of automobility (Urry, 2004), thereby increasing the likelihood that such drastic measures may in fact be successfully realized.     

On Two General Classes of Discrete Bivariate Distributions

In this article, we develop two general classes of discrete bivariate distributions. We derive general formulas for the joint distributions belonging to the classes. The obtained formulas for the joint distributions are very general in the sense that new families of distributions can be generated just by specifying the “baseline seed distributions.” The dependence structures of the bivariate distributions belonging to the proposed classes, along with basic statistical properties, are also discussed. New families of discrete bivariate distributions are generated from the classes. Furthermore, to assess the usefulness of the proposed classes, two discrete bivariate distributions generated from the classes are applied to analyze a real dataset and the results are compared with those obtained from conventional models.     

Bayesian Analysis of Skew Gaussian Spatial Models Based on Censored Data

The customary approach to spatial data modeling in the presence of censored data, is to assume the underlying random field is Gaussian. However, in practice, we often faced data that the exploratory data analysis shows the skewness and consequently, it violates the normality assumption. In such setting, the skew Gaussian (SG) spatial model is used to overcome this issue. In this article, the SG model is fitted based on censored observations. For this purpose, we adopt the Bayesian approach and utilize the Markov chain Monte Carlo algorithms and data augmentations to carry out calculations. A numerical example illustrates the methodology.