农户种植业风险及其认知比较研究

通过对浙江、上海、山东、湖北和安徽五个不同地区660户农户实地访问调查资料的分析发现:目前我国农户从事种植业生产经营的风险主要来源于气候等自然因素、农产品市场价格和农业生产资料价格;农户更关注农产品产量而非市场价格波动;在地区和作物层面上,具有不同生产特征和家庭特征的农户对种植业生产经营风险的认知具有一定的差异性;目前农户弱化种植业风险主要倾向于依靠自身的力量而较少依靠农业保险、农业组织及政府等外部力量。政府需要从完善信息发布体系、加强对农资市场管理、促进农村合作经济组织及农业保险的发展等方面入手,提高农户弱化生产经营风险的能力。     

新时期学报资料信息工作之管见

文章从信息时代的需要出发,主要阐述了学报资料搜集的依据、原则和方法,提出了有效的管理办法和开发利用学报资料的新思路。     

一种基于神经网络和决策树的信用评估新方法

分析了数据挖掘在国内外金融领域的应用及研究现状,提出了一种基于神经网络和决策树相结合的信用评估新方法。该方法通过RBF神经网络,进行条件属性裁减,并利用决策树抽取出评估规则。此方法利用神经网络的“黑箱”工作特性,选择重要条件属性,并利用决策树自动生成评估规则,大大提高了信用评估的效率和客观性。     

基于数据挖掘的客户关系分析评价系统

分析功能的深化是客户关系管理(CRM)的一大发展趋势,应用数据挖掘技术建立的CRM分析评价系统,可以对客户的行为以及市场趋势进行有效的分析,为企业的各种决策提供定性和定量的依据。该系统主要模块包括:客户细分模块、客户行为分析模块和市场趋势分析模块。以上各个模块涉及了企业关心的各种客户行为及市场行为,通过各个模块的分析,企业可以辨认出高端客户,理解各种客户行为模式,并掌握市场发展趋势以保证企业在激烈的竞争中立于不败之地。     

Missing data and forecasting in multivariate time series: An application of the common components dynamic linear model

Summary The paper deals with missing data and forecasting problems in multivariate time series making use of the Common Components Dynamic Linear Model (DLMCC), presented in Quintana (1985), and West and Harrison (1989). Some results are presented and discussed: exploiting the correlation between series, estimated by the DLMCC, the paper shows as it is possible to update state vector posterior distributions for the unobserved series. This is realized on the base of the updating of the observed series state vectors, for which the usual Kalman filter equations can be applied. An application concerning some Italian private consumption series provides an example of the model capabilities.     

Sampling Strategies for Toxic Air Contaminants

Annual concentrations of toxic air contaminants are of primary concern from the perspective of chronic human exposure assessment and risk analysis. Despite recent advances in air quality monitoring technology, resource and technical constraints often impose limitations on the availability of a sufficient number of ambient concentration measurements for performing environmental risk analysis. Therefore, sample size limitations, representativeness of data, and uncertainties in the estimated annual mean concentration must be examined before performing quantitative risk analysis. In this paper, we discuss several factors that need to be considered in designing field-sampling programs for toxic air contaminants and in verifying compliance with environmental regulations. Specifically, we examine the behavior of SO2, TSP, and CO data as surrogates for toxic air contaminants and as examples of point source, area source, and line source-dominated pollutants, respectively, from the standpoint of sampling design. We demonstrate the use of bootstrap resampling method and normal theory in estimating the annual mean concentration and its 95% confidence bounds from limited sampling data, and illustrate the application of operating characteristic (OC) curves to determine optimum sample size and other sampling strategies. We also outline a statistical procedure, based on a one-sided t-test, that utilizes the sampled concentration data for evaluating whether a sampling site is compliance with relevant ambient guideline concentrations for toxic air contaminants.     

Optimal sampling for repeated binary measurements

The authors consider the optimal design of sampling schedules for binary sequence data. They propose an approach which allows a variety of goals to be reflected in the utility function by including deterministic sampling cost, a term related to prediction, and if relevant, a term related to learning about a treatment effect To this end, they use a nonparametric probability model relying on a minimal number of assumptions. They show how their assumption of partial exchangeability for the binary sequence of data allows the sampling distribution to be written as a mixture of homogeneous Markov chains of order k. The implementation follows the approach of Quintana & Müller (2004), which uses a Dirichlet process prior for the mixture.     

Model Diagnostics for Remote Access Regression Servers

To protect public-use microdata, one approach is not to allow users access to the microdata. Instead, users submit analyses to a remote computer that reports back basic output from the fitted model, such as coefficients and standard errors. To be most useful, this remote server also should provide some way for users to check the fit of their models, without disclosing actual data values. This paper discusses regression diagnostics for remote servers. The proposal is to release synthetic diagnostics—i.e. simulated values of residuals and dependent and independent variables–constructed to mimic the relationships among the real-data residuals and independent variables. Using simulations, it is shown that the proposed synthetic diagnostics can reveal model inadequacies without substantial increase in the risk of disclosures. This approach also can be used to develop remote server diagnostics for generalized linear models.     

从分笔交易数据透视中国债券市场流动性

采用分笔交易数据,用相对买卖价差分析我国债券市场流动性,可以得出如下结论:各期限国债流动性差异不大,短期和长期国债流动性相对较好;国债买卖价差最小,可转债累计深度最大;债券市场流动性和波动性特征之间存在紧密的内在联系。     

Issues in applying recent CPMP ‘Points to Consider’ and FDA guidance documents with biostatistical implications

The International Conference on Harmonisation guideline ‘Statistical Principles for Clinical Trials’ was adopted by the Committee for Proprietary Medicinal Products (CPMP) in March 1998, and consequently is operational in Europe. Since then more detailed guidance on selected topics has been issued by the CPMP in the form of ‘Points to Consider’ documents. The intent of these was to give guidance particularly to non‐statistical reviewers within regulatory authorities, although of course they also provide a good source of information for pharmaceutical industry statisticians. In addition, the Food and Drug Administration has recently issued a draft guideline on data monitoring committees. In November 2002 a one‐day discussion forum was held in London by Statisticians in the Pharmaceutical Industry (PSI). The aim of the meeting was to discuss how statisticians were responding to some of the issues covered in these new guidelines, and to document consensus views where they existed. The forum was attended by industry, academic and regulatory statisticians. This paper outlines the questions raised, resulting discussions and consensus views reached. It is clear from the guidelines and discussions at the workshop that the statistical analysis strategy must be planned during the design phase of a clinical trial and carefully documented. Once the study is complete the analysis strategy should be thoughtfully executed and the findings reported. Copyright © 2003 John Wiley & Sons, Ltd.