Women's Health Care

No abstract available for this article.     

线性回归模型的一个新的随机约束岭估计

研究带随机先验信息的线性回归模型，提出一种新的随机约束岭估计，得到新的估计在均方误差矩阵意义下优于混合估计、普通岭估计、随机混合估计（Yalian,2008）和另一随机混合估计（富月，2003）的充要条件。理论结果与数值实验都表明：新的估计在均方误差矩阵意义下的性能是优良的。     

An Approach for Optimal Allocation of Safety Resources: Using the Knapsack Problem to Take Aggregated Cost‐Efficient Preventive Measures

On the basis of the combination of the well‐known knapsack problem and a widely used risk management technique in organizations (that is, the risk matrix), an approach was developed to carry out a cost‐benefits analysis to efficiently take prevention investment decisions. Using the knapsack problem as a model and combining it with a well‐known technique to solve this problem, bundles of prevention measures are prioritized based on their costs and benefits within a predefined prevention budget. Those bundles showing the highest efficiencies, and within a given budget, are identified from a wide variety of possible alternatives. Hence, the approach allows for an optimal allocation of safety resources, does not require any highly specialized information, and can therefore easily be applied by any organization using the risk matrix as a risk ranking tool.     

Environmental and life sciences: gene-environment networks optimization,games and control a survey on recent achievements

Abstract

A centrally important research area of computational biology, biotechnology and life sciences at all is devoted to modelling, prediction and dynamics of gene-expression patterns. However, this enterprise cannot be investigated in a satisfying way without the role of the environment, including the societies, members of the international community of nations. For a representation of the past, present and predicted future states, we also acknowledge the existence of uncertainties in modern technology and decision making, and the negotiations in solving societal problems and in international collaboration. We survey and closer explain recent advances in understanding the mathematical foundations and interdisciplinary implications of the newly introduced gene-environment networks; the main basis of our article is (Weber, Alparslan-Gk and Syler [to appear]). We integrate the important theme of environmental protection by joint international projects into the context of networks and their dynamics. As an example of environmental protection, we study CO₂ emissions, their implications for global warming by green-house effect, the reduction of both and the joint implementation requested for this purpose by Kyoto protocol. Given data from DNA microarray experiments and environmental records, we extract nonlinear ordinary differential equations which contain parameters that have to be determined. This is done by modern approximation and optimization. After this, time-discretized dynamical systems are studied by a combinatorial algorithm which detects the region of parametric stability. Finally, we analyze the landscape of gene-environment networks. Its structure and stability have a very important meaning for the understanding of life and social system and of the conductibility of common enterprises, for example, in the environmental sector. To represent the interactions between the project participants, we imply modern collaborative game theory, where the players may be individuals or companies or, in particular, nations. This pioneering work is practically motivated and theoretically elaborated; it is devoted to support improvements in the living conditions of people all over the world, especially, in health care, medicine, education, environmental protection and public awareness. The authors invite the interested readers to future research.     

电子商务网站动态模糊综合评价模型及实例

电子商务网站评价是衡量网站价值、分析网站优劣、指导网站建设的重要依据和方法。现有评价模型忽视了评价过程中的动态性、模糊性因素，存在很多缺点。动态模糊综合评价法基于动态模糊理论，模拟评价指标的动态性和模糊性，采用多级动态模糊递归方式，减少人为因素的影响。评价结果可以反映评价目标的动态发展趋势，且可以指导网站质量改进。本文最后通过对某商务网站的综合评价验证了该方法的有效性和实用性。     

Estimation of origin–destination trip rates in Leicester

The road system in region RA of Leicester has vehicle detectors embedded in many of the network's road links. Vehicle counts from these detectors can provide transportation researchers with a rich source of data. However, for many projects it is necessary for researchers to have an estimate of origin-to-destination vehicle flow rates. Obtaining such estimates from data observed on individual road links is a non-trivial statistical problem, made more difficult in the present context by non-negligible measurement errors in the vehicle counts collected. The paper uses road link traffic count data from April 1994 to estimate the origin–destination flow rates for region RA. A model for the error prone traffic counts is developed, but the resulting likelihood is not available in closed form. Nevertheless, it can be smoothly approximated by using Monte Carlo integration. The approximate likelihood is combined with prior information from a May 1991 survey in a Bayesian framework. The posterior is explored using the Hastings–Metropolis algorithm, since its normalizing constant is not available. Preliminary findings suggest that the data are overdispersed according to the original model. Results for a revised model indicate that a degree of overdispersion exists, but that the estimates of origin–destination flow rates are quite insensitive to the change in model specification.     

On a measure of dependence based on fisher's information matrix

A class of measures of dependence between two random vectors is defined, in terms of the canonical correlations obtained from Fisher's information matrix. Some basic properties are proved for this class of measures. Examples are given to illustrate that the class gives good measures, under normal models. Interesting measures are also arise for bivariate models where the correlation coefficient does not exist for some values of the parameters of the model.     

A two-state markov model

Markov chains are used to model binary urine test results. Taking advantage of the transition mechanism of Markov chains, missing observations can be incorporated in the analysis. Maximum likelihood estimates of transition probabilities are computed. Formulas for empirical Bayes procedures are given.     

Local improvement of best linear unbiased estimation and admissibility under the weakly singular gauss-markov model

Under the weakly singular Gauss-Markov model, the class of linearly admissible estimators for the expectation of the observable random vector with respect to the mean square error criterion is considered. It is demonstrated that this class admits linearly admissible estimators for an arbitrary estimable parametric function, which locally improve the best linear estimator with respect to the mean square error matrix criterion.