血管的三维重建

构建了血管的三维重建模型 ,并给出了模型的算法及其求解结果 .     

客户价值模型及对企业价值影响的研究

本文在对现有客户价值组成估算方法及企业股东价值(Shareholder Value,SHV)理念的局限性进行评价和分析的基础上,提出了计算客户整个生命周期价值(Lifetime Value,LTV)的客户价值(Customer Value,CV)模型;并简要分析了客户价值对提升企业价值的促进作用。通过运用CV模型计算出更准确的FCFF,本文亦提出了新的SHV计算模型。文章最后对模型的数据获得途径进行了简要介绍。     

欧元长期低迷的外在制约因素分析

现在美国的经济增长速度开始放缓 ,而欧盟的经济状况在经历两年的调整之后进入一个比较稳定的发展阶段。从理论上来讲欧元的汇率应该有一个坚挺的趋势 ,但事实却相反 ,欧元却一直走弱。本文通过欧盟和美国对欧元态度的对比 ,对这种现象做了一些分析。美国出于自身的利益考虑不希望欧元走强 ;而欧盟各国也都乐于看到欧元疲软 ;与此同时市场投资者也对欧元信心不足。这些态度其实成了解释欧元汇率的走势为什么屡屡出乎预测家的估计 ,一直保持相对弱势的关键原因     

组合预测误差信息矩阵研究

研究组合预测误差信息矩阵的结构与组合预测方法性质之间的联系,首次提出冗余信息概念,对最优组合预测方法的组合结构进行了研究。     

我国货币政策失效的原因分析及对策

1997年以来,我国的货币政策在经济增长中起到了一定的作用,但也存在一些失效,主要表现在利率机制、准备金政策、公开市场业务等方面存在缺陷。因此,必须不断完善我国的货币政策,以便更好地为经济增长提供政策指导。     

析科技翻译论著中汉语语法术语的误用

随着科学技术的发展 ,研究和探讨科技翻译的著作不断问世 ,但是目前有些论述科技英汉、汉英翻译的书籍在使用汉语语法术语方面不够正确。该文从词、句子成分和句的角度分析了汉语语法术语误用的情况。     

BATHTUB-TYPE CURVES IN RELIABILITY AND BEYOND

Finding optimal, or at least good, maintenance and repair policies is crucial in reliability engineering. Likewise, describing life phases of human mortality is important when determining social policy or insurance premiums. In these tasks, one searches for distributions to fit data and then makes inferences about the population(s). In the present paper, we focus on bathtub‐type distributions and provide a view of certain problems, methods and solutions, and a few challenges, that can be encountered in reliability engineering, survival analysis, demography and actuarial science.     

An alternative to model selection in ordinary regression

The weaknesses of established model selection procedures based on hypothesis testing and similar criteria are discussed and an alternative based on synthetic (composite) estimation is proposed. It is developed for the problem of prediction in ordinary regression and its properties are explored by simulations for the simple regression. Extensions to a general setting are described and an example with multiple regression is analysed. Arguments are presented against using a selected model for any inferences.     

Loss functions for estimation of extrema with an application to disease mapping

It is often of interest to find the maximum or near maxima among a set of vector‐valued parameters in a statistical model; in the case of disease mapping, for example, these correspond to relative‐risk “hotspots” where public‐health intervention may be needed. The general problem is one of estimating nonlinear functions of the ensemble of relative risks, but biased estimates result if posterior means are simply substituted into these nonlinear functions. The authors obtain better estimates of extrema from a new, weighted ranks squared error loss function. The derivation of these Bayes estimators assumes a hidden‐Markov random‐field model for relative risks, and their behaviour is illustrated with real and simulated data.     

On Rates of Convergence for Bayesian Density Estimation

Abstract.  We consider the problem of estimating a compactly supported density taking a Bayesian nonparametric approach. We define a Dirichlet mixture prior that, while selecting piecewise constant densities, has full support on the Hellinger metric space of all commonly dominated probability measures on a known bounded interval. We derive pointwise rates of convergence for the posterior expected density by studying the speed at which the posterior mass accumulates on shrinking Hellinger neighbourhoods of the sampling density. If the data are sampled from a strictly positive, α -Hölderian density, with α  ∈ ( 0,1] , then the optimal convergence rate n^{− α / (2 α +1)} is obtained up to a logarithmic factor. Smoothing histograms by polygons, a continuous piecewise linear estimator is obtained that for twice continuously differentiable, strictly positive densities satisfying boundary conditions attains a rate comparable up to a logarithmic factor to the convergence rate n ^−4/5 for integrated mean squared error of kernel type density estimators.