A hierarchy of lorenz curves based on the generalized tukey's lambda distribution

A hierarchy of Lorenz curves based on the generalized Tukey's Lambda distribution is proposed. Representations of the corresponding distribution and density function are also provided, together with popular inequality measures. Estimation methods are suggested. Finally, a comparison with other parametric families of Lorenz curves is established.     

A Similarity Measure Based on Species Proportions

ABSTRACT

There are several indices for measuring the similarity of two populations, including the ratio of the number of shared species to the number of distinct species (Jaccard's index) and the conditional probability of observing a shared species (Smith et al., 1996 Smith , W. , Solow , A. R. , Preston , P. E. ( 1996 ). An estimator of species overlap using a modified beta-binomial model. Biometrics 52 : 1472 – 1477 . [CSA] [CROSSREF] [Crossref], [Web of Science ®] , [Google Scholar]). However, these indices only take into account the number of species and species proportions of shared species. In this article, we propose a new similarity index which includes the species proportions of both the shared and non shared species in each population, and also propose a Nonparametric Maximum Likelihood Estimator (NPMLE) for this index. Bootstrap and delta methods are used to evaluate the standard errors of the NPMLE. Based on a loss function, we also compare a class of nonparametric estimators for the proposed index in various situations.     

Using a mixture model for multiple imputation in the presence of outliers: the 'Healthy for life' project

Summary.  We consider the problem of obtaining population-based inference in the presence of missing data and outliers in the context of estimating the prevalence of obesity and body mass index measures from the 'Healthy for life' study. Identifying multiple outliers in a multivariate setting is problematic because of problems such as masking, in which groups of outliers inflate the covariance matrix in a fashion that prevents their identification when included, and swamping, in which outliers skew covariances in a fashion that makes non-outlying observations appear to be outliers. We develop a latent class model that assumes that each observation belongs to one of K unobserved latent classes, with each latent class having a distinct covariance matrix. We consider the latent class covariance matrix with the largest determinant to form an 'outlier class'. By separating the covariance matrix for the outliers from the covariance matrices for the remainder of the data, we avoid the problems of masking and swamping. As did Ghosh-Dastidar and Schafer, we use a multiple-imputation approach, which allows us simultaneously to conduct inference after removing cases that appear to be outliers and to promulgate uncertainty in the outlier status through the model inference. We extend the work of Ghosh-Dastidar and Schafer by embedding the outlier class in a larger mixture model, consider penalized likelihood and posterior predictive distributions to assess model choice and model fit, and develop the model in a fashion to account for the complex sample design. We also consider the repeated sampling properties of the multiple imputation removal of outliers.     

Tests for assessment of agreement using probability criteria

For the assessment of agreement using probability criteria, we obtain an exact test, and for sample sizes exceeding 30, we give a bootstrap-t$t$ test that is remarkably accurate. We show that for assessing agreement, the total deviation index approach of Lin [2000. Total deviation index for measuring individual agreement with applications in laboratory performance and bioequivalence. Statist. Med. 19, 255–270] is not consistent and may not preserve its asymptotic nominal level, and that the coverage probability approach of Lin et al. [2002. Statistical methods in assessing agreement: models, issues and tools. J. Amer. Statist. Assoc. 97, 257–270] is overly conservative for moderate sample sizes. We also show that the nearly unbiased test of Wang and Hwang [2001. A nearly unbiased test for individual bioequivalence problems using probability criteria. J. Statist. Plann. Inference 99, 41–58] may be liberal for large sample sizes, and suggest a minor modification that gives numerically equivalent approximation to the exact test for sample sizes 30 or less. We present a simple and accurate sample size formula for planning studies on assessing agreement, and illustrate our methodology with a real data set from the literature.     

腐败的主观测评方法——以腐败感知指数为例

腐败测评是反腐败研究的重要组成部分,中国的腐败测评体系亟待发展。腐败测评有主观测评法和客观测评法两种研究思路。从统计机理和统计应用情况看,腐败的主观测评方法处于腐败测评研究的主流地位。本文介绍了腐败主观测评方法的基本思路、研究进展,并以腐败感知指数为例对其理论与应用情况进行了说明。     

区域主导产业评价指标与数学模型

以现有研究成果为基础,建立了区域主导产业评价指标体系;基于灰色聚类的思想,提出了评价区域主导产业优度的数学模型-定权聚类评估模型,并对河南省武陟县工业主导产业选择进行了实证研究。     

The zero-inflated Poisson model and the decayed, missing and filled teeth index in dental epidemiology

For frequency counts, the situation of extra zeros often arises in biomedical applications. This is demonstrated with count data from a dental epidemiological study in Belo Horizonte (the Belo Horizonte caries prevention study) which evaluated various programmes for reducing caries. Extra zeros, however, violate the variance–mean relationship of the Poisson error structure. This extra-Poisson variation can easily be explained by a special mixture model, the zero-inflated Poisson (ZIP) model. On the basis of the ZIP model, a graphical device is presented which not only summarizes the mixing distribution but also provides visual information about the overall mean. This device can be exploited to evaluate and compare various groups. Ways are discussed to include covariates and to develop an extension of the conventional Poisson regression. Finally, a method to evaluate intervention effects on the basis of the ZIP regression model is described and applied to the data of the Belo Horizonte caries prevention study.     

基于未确知测度方法的城市化水平评价研究

城市化水平是一个国家和地区经济、社会、文化、科技水平的重要标志,也是衡量国家和地区社会组织程度和管理水平的重要标志。实施城市化战略,推进城市化进程,是我国逐步摆脱不发达状态,实现现代化历史任务的目标和手段的统一,也是21世纪初我国现代化建设中的重要任务。因此,做好城市化水平的评价工作对于一个地区的发展有着重要的战略意义。论文研究了信息熵和未确知测度方法在城市化水平评价中的应用,给出了综合评价模型,并结合实例进行验证分析。     

学习型组织综合评价方法的研究

将学习型组织系统划分为学习、组织、人员、知识和信息五个子系统,对五个子系统进行了系统的分析,在此基础上建立了学习型组织综合评价指标体系,采用层次分析法确定了各指标的权重,并运用模糊综合评价法建立了学习型组织的模糊评价模型。该模型为衡量一个组织向学习型组织转变的程度提供了理论依据。     

关于我国股指期货设计方案的几点建议

本文主要阐述了作者对我国股指期货设计方案的一些看法。关于指数选择问题,本文认为不宜将现有的股价指数直接作为期货合约的交易基础,而应在对沪深两地现有成分股指数进行调整的基础上合成一个新指数;关于期货合约的设计,本文认为在确定乘数,最小波动点,合约交割月份,保证全水平及每日涨跌幅限制时,既要参考发达国家的经验,又要结合我国的国情;关于交易场所的选择,本文认为上海期货交易所应是首选。