Recent and classical goodness-of-fit tests for the Poisson distribution

We give a critical synopsis of classical and recent tests for Poissonity, our emphasis being on procedures which are consistent against general alternatives. Two classes of weighted Cramér–von Mises type test statistics, based on the empirical probability generating function process, are studied in more detail. Both of them generalize already known test statistics by introducing a weighting parameter, thus providing more flexibility with regard to power against specific alternatives. In both cases, we prove convergence in distribution of the statistics under the null hypothesis in the setting of a triangular array of rowwise independent and identically distributed random variables as well as consistency of the corresponding test against general alternatives. Therefore, a sound theoretical basis is provided for the parametric bootstrap procedure, which is applied to obtain critical values in a large-scale simulation study. Each of the tests considered in this study, when implemented via the parametric bootstrap method, maintains a nominal level of significance very closely, even for small sample sizes. The procedures are applied to four well-known data sets.     

论诉讼中的"二元"证明标准

诉讼中的证明标准问题是证据法学研究中的一个重要问题.近年来,一些学者从比较研究的角度提出在我国证据法中移植英美法上的"二元"证明标准.本文在理论和实践两个层次分析的基础上提出反驳理由,并指出,这种移植既无必要性,也缺乏可操作性.     

从解一个古典概率问题所想到的

文章给出一个古典概率问题的两个解法，从而导出几个有趣的等式。     

概率准则下的两期投资决策问题

概率准则是以期望收益率为导向的, 是某些情况下投资者的投资决策准则, 它具有一定 的现实指导意义. 在一般情况下, 证券收益率在不同时期的概率分布会不同而且相关. 因此, 提 出了一类概率准则下的两期投资决策问题, 建立了其数学模型. 对于证券收益率为连续及离散 型随机变量这两种情况分别进行了讨论, 给出了求解最优策略的方法及投资决策的步骤, 并举 例予以了说明.     

基于遗传算法的概率准则组合证券模拟求解

针对概率准则意义下的组合证券投资模型,采用随机模拟技术和遗传算法相结合的思 想, 设计出求解算法, 并用Matlab 语言实现. 求解算法适用于证券收益率服从任意分布的情 况, 甚至不考虑证券收益率分布, 用实际数据进行模拟和优化. 实例证明, 该算法有很好的 收敛性及较高的计算效率.     

A methodological strategy for a one-number census in the UK

As a result of lessons learnt from the 1991 census, a research programme was set up to seek improvements in census methodology. Underenumeration has been placed top of the agenda in this programme, and every effort is being made to achieve as high a coverage as possible in the 2001 census. In recognition, however, that 100% coverage will never be achieved, the one-number census (ONC) project was established to measure the degree of underenumeration in the 2001 census and, if possible, to adjust fully the outputs from the census for that undercount. A key component of this adjustment process is a census coverage survey (CCS). This paper presents an overview of the ONC project, focusing on the design and analysis methodology for the CCS. It also presents results that allow the reader to evaluate the robustness of this methodology.     

两类广义卷积

把定义在半直线Ｒ＋＝［０，∞）上概率测度的广义卷积推广到了紧空间Ｒ＋＝［０，∞］上．讨论了与连续性、单位元有关的性质．根据单位元的可能性，导出了两类广义卷积，研究了它们之间的关系．比较了本文所用的推广方法与Ｕｒｂａｎｉｋ的推广方法之间的联系．     

Asymptotic properties of a generalized regression-type predictor of a finite population variance in probability sampling

A system of predictors for estimating a finite population variance is defined and shown to be asymptotically design-unbiased (ADU) and asymptotically design-consistent (ADC) under probability sampling. An asymptotic mean squared error (MSE) of a generalized regression-type predictor, generated from the system, is obtained. The suggested predictor attains the minimum expected variance of any design-unbiased estimator when the superpopulation model is correct. The generalized regression-type predictor and the predictor suggested by Mukhopadhyay (1990) are compared.     

Fusion of Intelligence Information: A Bayesian Approach

The attack that occurred on September 11, 2001 was, in the end, the result of a failure to detect and prevent the terrorist operations that hit the United States. The U.S. government thus faces at this time the daunting tasks of first, drastically increasing its ability to obtain and interpret different types of signals of impending terrorist attacks with sufficient lead time and accuracy, and second, improving its ability to react effectively. One of the main challenges is the fusion of information, from different sources (U.S. or foreign), and of different types (electronic signals, human intelligence. etc.). Fusion thus involves two very distinct and separate issues: communications, i.e., ensuring that the different U.S. and foreign intelligence agencies communicate all relevant and accurate information in a timely fashion and, perhaps more difficult, merging the content of signals, some "sharp" and some "fuzzy," some dependent and some independent into useful information. The focus of this article is on the latter issue, and on the use of the results. In this article, I present a classic probabilistic Bayesian model sometimes used in engineering risk analysis, which can be helpful in the fusion of information because it allows computation of the posterior probability of an event given its prior probability (before the signal is observed) and the quality of the signal characterized by the probabilities of false positive and false negative. Experience suggests that the nature of these errors has been sometimes misunderstood; therefore, I discuss the validity of several possible definitions.     

时间贝叶斯网络及其概率推理

针对贝叶斯网络应用中出现的循环和动态问题,研究贝叶斯网络的时间扩展.给出了时间贝叶斯网络的定义;探讨了时间贝叶斯网络中环的存在合理性判断问题;给出了时间贝叶斯网络的概率推理算法,应用示例说明了方法的可行性.