RIDICULING THE ‘WHITE BREAD ORIGINAL’

The 1994 US Supreme Court decision in Luther Campbell et al. v. Acuff-Rose Music, Inc., written by Justice David Souter, reversed a lower court decision and argued in favor of the rap group 2 Live Crew's playful critique of Roy Orbison's ‘Oh Pretty Woman’ by its function as parody. This essay seeks to contextualize that decision by showing the roots of 2 Live Crew's recording in the practice of ‘covering’ – the re-recording of an existent popular composition – and thus the possibilities for redefining authorship that arose with the advent of digital technology. The compositional techniques allowed by computer programs led to the proliferation of sampling in the hip-hop community, thereby liberating sounds from the original content and reconfiguring them in new songs. The technique allowed a critical, and in some cases adversarial, stance to be taken towards long-standing Western definitions of authorship and ownership. 2 Live Crew added to this rich stew of possibilities the familiar and time-tested genre of parody. Their piece took what one judge referred to as the ‘white bread original’ of the Roy Orbison record and twisted about the implicit point of view with regard to gender and sexuality. Discussion of the legal complications that followed upon the suing of the group by the holder of the copyright in the Orbison song, Acuff-Rose Music, Inc., includes the apparently sanctioned use of the song in the Disney-produced film Pretty Woman as well as the use of other Orbison material in director David Lynch's Blue Velvet. The essay concludes with suggestions as to how the language of Justice Souter's decision allows not only for future parodies but also a reinvigoration of speech, one which calls into question power relationships codified in US copyright statutes.     

基于加权组合和最小二乘法改进的GM(2,1)模型

文章通过分析指出了GM(2,1)模型存在灰微分方程与白化方程无法匹配以及默认经过初始值点的缺陷;利用权值p1、p2对一阶灰导数和背景值进行加权组合,建立了GM(2,1)模型的一种改进形式--GM(2,1,p1,p2模型,利用最小二乘法确定系统最终参数.实例验证结果表明,改进GM(2,1)模型具有更高的预测精度.     

Comparing several experimental groups with a control in the multivariate case

This paper presents a multivariate extension of Dunnett's test for comparing simultaneously k treatment group means with a single control group mean. A test based on Hotelling T²statistics is presented and approximate critical values are evaluated for the case of equal numbers of observations in each group, for the .05 and .01 levels of significance, for 1 to 5 variates, for 1 to 10 treatment groups, and for varying degrees of freedom. The accuracy of the procedure for generating approximate critical values is assessed via simulation studies conducted for selected cases and an example is presented using real data.     

First‐order bias correction for fractionally integrated time series

Most of the long memory estimators for stationary fractionally integrated time series models are known to experience non‐negligible bias in small and finite samples. Simple moment estimators are also vulnerable to such bias, but can easily be corrected. In this article, the authors propose bias reduction methods for a lag‐one sample autocorrelation‐based moment estimator. In order to reduce the bias of the moment estimator, the authors explicitly obtain the exact bias of lag‐one sample autocorrelation up to the order n⁻¹. An example where the exact first‐order bias can be noticeably more accurate than its asymptotic counterpart, even for large samples, is presented. The authors show via a simulation study that the proposed methods are promising and effective in reducing the bias of the moment estimator with minimal variance inflation. The proposed methods are applied to the northern hemisphere data. The Canadian Journal of Statistics 37: 476–493; 2009 © 2009 Statistical Society of Canada     

Finding environmentally important industry clusters: Multiway cut approach using nonnegative matrix factorization

This paper proposes an optimal combinatorial method for finding groups of industries with relatively large CO₂ emissions through industrial relations. Using an economic input–output table, we estimated a non-symmetric matrix describing how much CO₂ is emitted in producing the commodity of industry i, which was purchased to produce commodity of industry j, to meet the final demand for a specific commodity. A symmetric strength of relations matrix describing the CO₂ emissions associated with the industrial relations was further estimated using the non-symmetric matrix. The strength of relations matrix can be viewed as a representation of the supply-chain network of the final commodity. In this study, we estimated the strength of relations matrix associated with the final demand for automobiles and applied the multiway cut approach using nonnegative matrix factorization to the matrix in order to find environmentally important industry clusters in the Japanese automobile supply chain. According to our empirical results, the optimal number of industry clusters is 19, and 4 industry clusters are playing a key role in CO₂ emission reduction.     

Dependence function for continuous bivariate densities

The notion of cross-product ratio for discrete two-way contingency table is extended to the case of continuous bivariate densities. This results in the “local dependence function” that measues the margin-free dependence between bivariate random variables. Properties and examples of the dependence function are discussed. The bivariate normal density plays a special role since it has constant dependence. Continuous bivariate densities can be constructed by specifying the dependence function along with two marginals in analogy to the construction of two-way contingency tables given marginals and patterns of interaction. The dependence function provides a partial ordering on bivariate dependence.     

LOG-PERIODOGRAM ESTIMATION OF LONG MEMORY VOLATILITY DEPENDENCIES WITH CONDITIONALLY HEAVY TAILED RETURNS

ABSTRACT

Many recent papers have used semiparametric methods, especially the log-periodogram regression, to detect and estimate long memory in the volatility of asset returns. In these papers, the volatility is proxied by measures such as squared, log-squared, and absolute returns. While the evidence for the existence of long memory is strong using any of these measures, the actual long memory parameter estimates can be sensitive to which measure is used. In Monte-Carlo simulations, I find that if the data is conditionally leptokurtic, the log-periodogram regression estimator using squared returns has a large downward bias, which is avoided by using other volatility measures. In United States stock return data, I find that squared returns give much lower estimates of the long memory parameter than the alternative volatility measures, which is consistent with the simulation results. I conclude that researchers should avoid using the squared returns in the semiparametric estimation of long memory volatility dependencies.     

C2C卖家的诚信行为模式及其动态性研究

现有电子商务的信用评价体系单一维度的特点使得评级体系难以准确衡量、比较店铺在各维度之间的差异及其变化。为了提高C2C电子商务信用评级体系的信息揭示作用,本文试图从多维度指标分析店铺的诚信行为模式及其动态性。本文对淘宝7大行业不同信用等级的卖家的诚信指标数据进行聚类分析表明,店铺在动态评分、信用等级、好评率上分别具有六类不同的静态组合特征,信用积分在解释店铺诚信状态上弱于动态评分和好评率指标。动态模式分析表明,店铺的好评率、动态评分指标及其与同业行业比值会呈现出三个不同的组合变化趋势。最后本文提出对现有的评价体系改进,以体现店铺之间在模式上的差异,从而真实展现卖家的诚信水平。     

中国C2C交易市场电子服务质量对顾客忠诚的影响——以顾客满意和顾客价值为中介变量

通过构建整合性的理论研究模型，揭示了C2C交易市场电子服务质量、顾客满意、顾客价值以及顾客忠诚之间相互作用的机理。并对中国具有C2C网上购物经验的用户进行问卷调查，建立结构方程模型，采用验证性因子分析法实证检验研究假设。研究结果发现：（1）C2C网站的电子服务质量对顾客满意和顾客价值产生显著的正向影响；（2）C2C卖家的电子服务质量对顾客满意产生显著的正向影响，对顾客价值的影响不显著；（3）顾客满意和顾客价值都对顾客忠诚产生显著的正向影响；（4）确认了顾客满意和顾客价值在C2C交易市场电子服务质量和顾客忠诚之间的中介效应。根据研究结论对C2C交易网站和网上卖家提高电子服务质量和顾客忠诚提出一些富有决策指导意义的对策和建议。