On an adaptive version of the Metropolis–Hastings algorithm with independent proposal distribution

In this paper, we present a general formulation of an algorithm, the adaptive independent chain (AIC), that was introduced in a special context in Gåsemyr et al . [ Methodol. Comput. Appl. Probab. 3 (2001)]. The algorithm aims at producing samples from a specific target distribution Π, and is an adaptive, non-Markovian version of the Metropolis–Hastings independent chain. A certain parametric class of possible proposal distributions is fixed, and the parameters of the proposal distribution are updated periodically on the basis of the recent history of the chain, thereby obtaining proposals that get ever closer to Π. We show that under certain conditions, the algorithm produces an exact sample from Π in a finite number of iterations, and hence that it converges to Π. We also present another adaptive algorithm, the componentwise adaptive independent chain (CAIC), which may be an alternative in particular in high dimensions. The CAIC may be regarded as an adaptive approximation to the Gibbs sampler updating parametric approximations to the conditionals of Π.     

Optimal scaling of Metropolis algorithms: Heading toward general target distributions

The authors provide an overview of optimal scaling results for the Metropolis algorithm with Gaussian proposal distribution. They address in more depth the case of high‐dimensional target distributions formed of independent, but not identically distributed components. They attempt to give an intuitive explanation as to why the well‐known optimal acceptance rate of 0.234 is not always suitable. They show how to find the asymptotically optimal acceptance rate when needed, and they explain why it is sometimes necessary to turn to inhomogeneous proposal distributions. Their results are illustrated with a simple example.     

国外票据市场的发展及对我国的启示

随着现代经济的发展 ,票据作为一种支付信用结算工具 ,其低风险、高流动性的短期投资和融资功能日益受到企业、商业银行及广大投资者的重视 ,各种票据逐渐成为企业短期融资、银行提高资产负债的流动性管理和风险管理、满足投资者短期投资需要的重要货币市场工具。分析和研究票据市场发展现状及其特点 ,对我国票据市场发展有积极的借鉴意义。     

中国股票市场价格波动特征分析

在股票市场中最令人捉摸不定,也最具有吸引力的是波动不已的股票价格。文章对中国股票市场价格波动的分析是从1997年9月展开至2002年10月,其间恰逢中国股市经历了一段从牛市的繁荣到熊市的萧条的过程,两种泾渭分明的市场氛围恰好提供了一个深入研究股票市场价格波动特征的有利契机。遵循经济控制论研究的思路,文章采用了理论分析、市场交易数据的实证研究等技术手段对中国股票市场价格波动进行了研究,通过运用经济控制论的方法建立理论模型,以上海股市和深圳股市的综合指数为样本,对中国股票市场系统本身的波动特征和稳定性进行了量化分析。     

论中国证券市场监管低效的制度性因素

分析了作为政府强制性的制度安排,中国证券市场在发展过程中产生的市场不规范问题,认为证券市场监管制度的低效运行是问题产生的主要原因。而监管困境的背后则是制度的缺陷,主要表现为两个方面:一是监管当局政策目标与监管目标的冲突;二是以个人和企业信用为核心的信用管理体系的缺失。     

India’s Social Development in a Decade of Reforms: 1990–91/1999–2000

The economic reforms initiated in India in 1991 have brought about visible upliftment of economic conditions of the country. This paper examines if the economic process is associated with an enhancement of India’s social development in equal measure in the reform decade of nineties. Ray (1989) considered thirteen social indicators of India and constructed the country’s social development index (SDI) as a certain weighted average of the selected indicators, for the years between 1950–51 and 1975–76. The present work broadly follows Ray (1989) in tracking the social development in the decade of economic reforms from 1990–91 to 1999–2000. The movement of SDI in nineties has been compared with the movements of India’s per capita income and plan expenditure on the social sector. The results show that though there has been growth in the social sector, it is not by far quite encouraging and perhaps more needs to be done in the social sector. The views expressed in the article are those of the author and not of the institution he serves.     

我国上市公司社会责任与企业价值关联性分析——以房地产开发与经营业为例

基于财务报告的指标体系、运用主成分分析的方法，对在我国深、沪上市的房地产开发与经营业公司企业价值（以托宾Q衡量）与所建指标体系之间的关系进行实证分析。分析结果表明：样本公司财务报告所反映的其社会责任履行情况与其企业价值相关关系显著，这一实证结果表明企业的社会责任履行对现代企业来说，已经不是一个可有可无的附属品，在企业生存和发展过程中发挥着越来越重要的作用。     

现代化的扩散与乡村政治文化的变迁——以改革开放以来安徽和县浏塘村为例

文章遵循从基本理论到实证调查再到一般性结论的研究路径,从实证的角度去描述安徽一个普通村庄因现代化的扩散而导致的乡村政治文化的变迁,从而试图说明现代化的扩散对乡村政治文化变迁的影响。     

Tree health mapping with multispectral remote sensing data at UC Davis, California

Tree health is a critical parameter for evaluating urban ecosystem health and sustainability. Traditionally, this parameter has been derived from field surveys. We used multispectral remote sensing data and GIS techniques to determine tree health at the University of California, Davis. The study area (363 ha) contained 8,962 trees of 215 species. Tree health conditions were mapped for each physiognomic type at two scales: pixel and whole tree. At the pixel scale, each tree pixel within the tree crown was classified as either healthy or unhealthy based on vegetation index values. At the whole tree scale, raster based statistical analysis was used to calculate tree health index which is the ratio of healthy pixels to entire tree pixels within the tree crown. The tree was classified as healthy if the index was greater than 70%. Accuracy was checked against a random sample of 1,186 trees. At the whole tree level, 86% of campus trees were classified as healthy with 88% mapping accuracy. At the pixel level, 86% of the campus tree cover was classified as healthy. This tree health evaluation approach allows managers to identify the location of unhealthy trees for further diagnosis and treatment. It can be used to track the spread of disease and monitor seasonal or annual changes in tree health. Also, it provides tree health information that is fundamental to modeling and analysis of the environmental, social, and economic services produced by urban forests.     

A modified false discovery rate multiple-comparisons procedure for discrete data, applied to human immunodeficiency virus genetics

Summary.  To help to design vaccines for acquired immune deficiency syndrome that protect broadly against many genetic variants of the human immunodeficiency virus, the mutation rates at 118 positions in HIV amino-acid sequences of subtype C versus those of subtype B were compared. The false discovery rate (FDR) multiple-comparisons procedure can be used to determine statistical significance. When the test statistics have discrete distributions, the FDR procedure can be made more powerful by a simple modification. The paper develops a modified FDR procedure for discrete data and applies it to the human immunodeficiency virus data. The new procedure detects 15 positions with significantly different mutation rates compared with 11 that are detected by the original FDR method. Simulations delineate conditions under which the modified FDR procedure confers large gains in power over the original technique. In general FDR adjustment methods can be improved for discrete data by incorporating the modification proposed.