Pitfalls in using Weibull tailed distributions

By assuming that the underlying distribution belongs to the domain of attraction of an extreme value distribution, one can extrapolate the data to a far tail region so that a rare event can be predicted. However, when the distribution is in the domain of attraction of a Gumbel distribution, the extrapolation is quite limited generally in comparison with a heavy tailed distribution. In view of this drawback, a Weibull tailed distribution has been studied recently. Some methods for choosing the sample fraction in estimating the Weibull tail coefficient and some bias reduction estimators have been proposed in the literature. In this paper, we show that the theoretical optimal sample fraction does not exist and a bias reduction estimator does not always produce a smaller mean squared error than a biased estimator. These are different from using a heavy tailed distribution. Further we propose a refined class of Weibull tailed distributions which are more useful in estimating high quantiles and extreme tail probabilities.     

公司治理对盈余质量的影响——来自中国上市公司的经验证据

公司治理理论的一个重要观点是上市公司的治理质量越高,会计盈余对投资者的决策有用性越强.使用会计盈余的信息含量作为衡量盈余质量高低的判断标准,基于南开大学中国上市公司治理指数将样本公司分为公司治理好的公司和公司治理差的公司,使用盈余一报酬模型,选取我国深、沪市2005年、2006年符合条件的上市公司为样本,运用描述性统计、回归分析等方法对公司治理与盈余质量之间的关系进行实证研究.统计结果表明,公司治理好的公司与公司治理差的公司的盈余信息含量确实存在显著差异:公司治理越好,盈余变化的反应系数越大,即盈余信息含量越高.     

农村产业结构调整与农民收入增长关系实证研究——以江苏省为例

在阐述农村产业结构基本理论的基础上,从农村产业第一、二、三产业的结构角度研究农村产业结构调整与农民收入增长的关系。以江苏省为例,选用农村产业结构层次系数考察农村产业结构调整的进程,用农村居民人均纯收入来衡量农民收入状况,对农村产业结构调整与农民收入增长的关系进行实证研究。结论表明,农村产业结构调整对农民收入增长的促进作用显著。农村产业结构调整是农民收入增长变化的Granger原因,即农村产业结构调整促进了农民收入增长的加快。     

贵州城乡经济一体化现状、问题及对策研究

本文首先分析了城乡经济一体化的基本内涵,同时主要采用城乡居民收入差异系数、城乡居民恩格尔系数差异系数、二元对比系数以及城乡居民收入差异倍数、城乡居民积累差异倍数五个基本指标分析了贵州省1978年-2006年城乡差异的现状。分析得出贵州省存在较显著的城乡二元经济结构,城乡经济一体化任重而道远。     

棘腹蛙性腺的发育与周年变化

本文讨论了湘西棘腹蛙的性腺发育与性腺成熟系数的季节变化。实验材料来自204只幼蛙和成蛙（其中雌蛙122只，雄蛙82只）。卵巢的发育可分为6期，雌性的性成熟年龄为3年；精巢的发育可分为5期，雄性的性成熟年龄为2年。每年的5～8月为棘腹蛙的繁殖季节。同时，在文章中也描述了发育各期生殖细胞的主要形态结构。     

Risk Assessment for Hospital-Acquired Diseases: A Risk-Theory Approach

We introduce a new approach to hospital-acquired disease risk assessment from public health databases. In a spirit similar to actuarial risk theory, we define an adjustment coefficient that can quantify the risk associated with a hospital department, allowing comparisons of similar departments. The adjustment coefficient characterizes the tail of the distribution of the total patient length of stay in a department before the first disease event occurs. We show that this coefficient is the solution of a Lundberg-like equation, and we provide a nonparametric estimation procedure for this measure, based on a Cramér-Lundberg approximation for the tail of the distribution. Using simulations, we provide evidence of the robustness of the approximation to various individual risk models. In addition, we illustrate the relevance of this approach by evaluating the risk associated with a standard patient safety indicator in 20 hospitals of southeastern France.     

中国城乡收入分布动态演进及经验检验

 本文利用“中国营养和健康调查”家庭平均收入的模块数据，采用核密度估计、累积分布函数、洛伦茨曲线等方法刻画我国城乡居民收入分布的动态演进，结果表明，大多数家庭都分享了我国经济快速增长带来的成果，其中高收入阶层比低收入阶层更多地分享了经济成果，城市居民比农村居民更多地分享了经济成果。进一步地，非参数假设检验和相对偏差估计结果表明，N. C. Kakwani的三参数函数和简易公式的基尼系数估计精度较高，广义Logistic分布函数是估计城乡居民收入分布的可行选择。     

新疆区域经济差异及其影响因素分析

采用洛伦茨曲线、基尼系数、泰尔指数、非参数分析法及Shorrocks转换矩阵对1978-2009年新疆区域经济差异进行分析,结果表明新疆区域经济发展水平差异呈逐渐加大的趋势,其主要是由于新疆不同区域间发展不平衡造成的；同时,新疆区域经济发展的不平衡是在区域经济格局越来越稳定的惯性中发生的.根据对新疆区域经济差异影响因素的分析,应加大对新疆固定资产投资,并注意投资区域布局的合理化；加快新疆教育事业发展,努力实现教育与经济的协调发展；加快新疆产业结构的调整,推进产业结构的合理化和高级化.     

A note on measures of similarity based on centrality

This note presents a measure of similarity between connected nodes in terms of centrality based on Euclidean distances, and compares it to ‘assortative mixing’ [Newman, M.E.J., 2002. Assortative mixing in networks. Physical Review Letters 89, 208701], which is based on Pearson correlation coefficient. This study suggests that the measure based on Euclidean distances may be more appropriate for relatively smaller (N < 500) and denser networks.     

Adaptive Gaussian Markov random fields with applications in human brain mapping

Summary.  Functional magnetic resonance imaging has become a standard technology in human brain mapping. Analyses of the massive spatiotemporal functional magnetic resonance imaging data sets often focus on parametric or non-parametric modelling of the temporal component, whereas spatial smoothing is based on Gaussian kernels or random fields. A weakness of Gaussian spatial smoothing is underestimation of activation peaks or blurring of high curvature transitions between activated and non-activated regions of the brain. To improve spatial adaptivity, we introduce a class of inhomogeneous Markov random fields with stochastic interaction weights in a space-varying coefficient model. For given weights, the random field is conditionally Gaussian, but marginally it is non-Gaussian. Fully Bayesian inference, including estimation of weights and variance parameters, can be carried out through efficient Markov chain Monte Carlo simulation. Although motivated by the analysis of functional magnetic resonance imaging data, the methodological development is general and can also be used for spatial smoothing and regression analysis of areal data on irregular lattices. An application to stylized artificial data and to real functional magnetic resonance imaging data from a visual stimulation experiment demonstrates the performance of our approach in comparison with Gaussian and robustified non-Gaussian Markov random-field models.