Trivial Two-Stage Group Testing with High Error Rates

Given a population of cardinality q ^r that contains a positive subset P of cardinality p, we give a trivial two-stage method that has first stage pools each of which contains q ^{r – 2} objects. We assume that errors occur in the first stage. We give an algorithm that uses the results of first stage to generate a set CP of candidate positives with |CP| (r + 1)q. We give the expected value of |CPP|. At most (r + 1)q trivial second stage tests are needed to identify all the positives in CP. We assume that the second stage tests are error free.     

Applications in business,medical and industrial statistics of bi-aspect nonparametric tests for location problems

Starting from the theory of the Nonparametric Combination of Dependent Permutation Tests (Pesarin, 1992, 2001), Marozzi (2002a, b) proposed two bi-aspect nonparametric tests for the two-sample and the multi-sample location problems. These tests are shown by simulation to be remarkably more powerful than the traditional parametric and permutation competitors (which can be seen as uni-aspect tests) under heavy-tailed and skewed distributions. After a brief presentation of the bi-aspect idea to location testing problems, three actual applications are discussed. The first one is a problem of business statistics and deals with the analysis of time for service calls. The second one is in medical statistics and deals with the analysis of the effect of cigarette smoking on maternal airway function during pregnancy. The third one is in industrial statistics and deals with the analysis of the setting of machines that produce steel ball bearings. The bi-aspect testing allows us to draw deeper and more informative inference than that allowed by traditional competitors.Marco Marozzi: Part of the research was done when the author was in Dipartimento di Scienze Statistiche, Universitá di Bologna, Italy.     

基于遗传算法的分辨系数的优化方法

灰关联分析中分辨系数的选取会影响到分析结果的信息分辨程度,甚至灰关联序。把遗传算法和差异信息熵理论结合给出了优化分辨系数的方法。此方法把分辨系数作为优化变量,关联度序列的熵最小为优化目标,利用遗传算法的优化机制获得优化的分辨系数。最后,给出了一个计算实例。     

基于遗传算法的前沿生产函数构造及其应用

效率测度分析是评价企业经营管理的重要指标,其求解往往同构造前沿生产函数联系 在一起. 对采用遗传算法构造前沿生产函数进行了研究,电力工业的实证效率测度分析以及与 非参数方法的比较结果验证了本方法的正确性和实用性,可为电力工业的决策者和这一领域 的研究人员提供参考.     

不确定条件下不同交货期窗口的Job Shop 调度

研究了具有不同交货期窗口的Job Shop 的提前/ 拖期调度问题,并考虑了处理时间的不确定 性,采用三角模糊数表示处理时间的不确定性,提出了基于遗传算法的求解算法. 仿真实验验证了 算法的有效性.     

Comparing the Fisher information in record data and random observations

We compare the Fisher information (FI) contained in the firstn record values and record times with the FI inn i. i. d. observations. General results are established for exponential family and Weibull type setups, and a summary table is provided listing several common distributions. We show that the FI in record data improves notably once the record times are included, often changing from being less to being equal or greater than the FI in a random sample of the same size. The behavior in the Weibull case is surprising. There it depends onn, whether the record or the i.i. d. observations have more FI. We propose new estimators based on record data. The results may be of interest in some life testing situations. Supported in part by Fondo Nacional de Desarrollo Cientifico y Tecnologico (FONDECYT) grant # 1010222 of Chile.     

On some stepdown procedures with application to consistent variable selection in linear regression

The paper considers the problem of consistent variable selection with the use of stepdown procedures in the classical linear regression model and for the model with dependent errors. The stated results complete the results obtained by Bunea et al. [Consistent variable selection in high dimensional regression via multiple testing. J Stat Plann Inference. 2006;136(12):4349–4364].     

翻译测试的外延与内涵

在定义翻译和测试的基础上,确定了翻译测试的内涵。为了满足翻译测试研究活动的操作性要求,本讨论把翻译定义为翻译活动主体的工作表现或工作实力或发展性向,把测试定义为由准备、实施和跟踪研究构成的过程。对于翻译测试,准备过程的内容主要包括总测试规划的论证与制定、实施条件的规定、刺激物的标准化、人员的培训、有效性依据和证据的采集、结果有效使用措施的制定等。实施过程的主要内容包括标准化环境条件的满足、标准化任务的呈献以及任务完成情况的评定等,跟踪研究过程的主要任务是对测试项目执行的效应进行检测。在讨论翻译测试与教育和心理测试、语言测试以及翻译研究关系的基础上,考虑到翻译测试的内涵,提出不宜把翻译测试作为语言测试的一个分支,建议把翻译测试作为应用翻译学的一个分支。     

Consistent Moment Selection Procedures for Generalized Method of Moments Estimation

This paper considers a generalized method of moments (GMM) estimation problem in which one has a vector of moment conditions, some of which are correct and some incorrect. The paper introduces several procedures for consistently selecting the correct moment conditions. The procedures also can consistently determine whether there is a sufficient number of correct moment conditions to identify the unknown parameters of interest. The paper specifies moment selection criteria that are GMM analogues of the widely used BIC and AIC model selection criteria. (The latter is not consistent.) The paper also considers downward and upward testing procedures. All of the moment selection procedures discussed in this paper are based on the minimized values of the GMM criterion function for different vectors of moment conditions. The procedures are applicable in time-series and cross-sectional contexts. Application of the results of the paper to instrumental variables estimation problems yields consistent procedures for selecting instrumental variables.