Sensitivity Analysis and Estimation of Extreme Tail Behavior in Two‐Dimensional Monte Carlo Simulation

Two‐dimensional Monte Carlo simulation is frequently used to implement probabilistic risk models, as it allows for uncertainty and variability to be quantified separately. In many cases, we are interested in the proportion of individuals from a variable population exceeding a critical threshold, together with uncertainty about this proportion. In this article we introduce a new method that can accurately estimate these quantities much more efficiently than conventional algorithms. We also show how those model parameters having the greatest impact on the probabilities of rare events can be quickly identified via this method. The algorithm combines elements from well‐established statistical techniques in extreme value theory and Bayesian analysis of computer models. We demonstrate the practical application of these methods with a simple example, in which the true distributions are known exactly, and also with a more realistic model of microbial contamination of milk with seven parameters. For the latter, sensitivity analysis (SA) is shown to identify the two inputs explaining the majority of variation in distribution tail behavior. In the subsequent prediction of probabilities of large contamination events, similar results are obtained using the new approach taking 43 seconds or the conventional simulation that requires more than 3 days.     

Generalised Smooth Tests of Goodness of Fit Utilising L‐moments

In this paper we present a semiparametric test of goodness of fit which is based on the method of L‐moments for the estimation of the nuisance parameters. This test is particularly useful for any distribution that has a convenient expression for its quantile function. The test proceeds by investigating equality of the first few L‐moments of the true and the hypothesised distributions. We provide details and undertake simulation studies for the logistic and the generalised Pareto distributions. Although for some distributions the method of L‐moments estimator is less efficient than the maximum likelihood estimator, the former method has the advantage that it may be used in semiparametric settings and that it requires weaker existence conditions. The new test is often more powerful than competitor tests for goodness of fit of the logistic and generalised Pareto distributions.     

农村金融市场的“双失灵”和帕累托改进——基于政策扶持视角

我国农村金融市场一直存在市场失灵和政府失灵的＂双失灵＂问题,而目前小额贷款公司、农村信用社的改革和发展思路都难以对改善农村金融市场状况奏效。鉴于农村金融市场的特殊性和复杂性,只有建立以政策扶持为先导、面向金融机构全面开放的市场竞争格局,才能从根本上促进农村金融市场有序、健康发展。     

我国农村金融市场效率内涵研究

以提高农村金融市场效率的农村金融改革不可回避的一个问题就是:如何全面认识农村金融市场效率。文章结合西方理论界对市场效率、金融市场效率的研究及我国学者的研究,提出了我国金融市场效率的内涵及评价角度。     

基于战略的供应链管理的企业合作博弈分析

在供应链管理下,大量的重复博弈及有效的信息沟通,使得供应链管理的合作机制得以实现。供应链与供应链之间的竞争使得供应链节点企业之间的竞争具有了正数和博弈的基础,为供应链的帕累托改进创造了条件。随着合作博弈过程的逐步深化,使得供应链的合作博弈机制具有可持续性。     

高压头小流量单级轴流风扇的设计和优化方法

本文针对国产３００ＭＷ汽轮发电机冷却用单级轴流风扇的改型设计，分别对有后导叶和无导叶两种不同方案轴流风扇进行了理论研究及实验分析．对其在高压头、小流量的条件下使用作了性能上的比较，同时利用优化方法找出该风扇动叶的扭曲规律，并对叶轮直径、轮毂比等关键设计参数的选取进行了分析研究．     

绵阳市农业区域开发规划的目标设计及方案优化研究

该项研究应用经济预测和线性规划等方法，对涉及绵阳市农村经济发展的主要指标进行了预测，对未来“八五”末、“九五”末和“二○二○年”各时段的大农业生产进行了总体规划及其方案优化，为绵阳市农业区域开发提供了科学的依据。     

PPS分层抽样时样本单位数的设计

讨论了PPS分层抽样时,样本单位数的设计问题。对一种常见模型,给出了一个方便有效的分配规则。     

经济优化过程中的交易成本

科斯在《企业的本质》中 ,首次用交易成本解释企业代替市场的原因。当把科斯的交易成本理论用来解释帕累托效率和经济制度变迁时 ,新古典经济学的框架不再成立 ,现实的经济过程只能达到帕累托“次”优 ;同时 ,交易成本也阻碍了经济制度变迁的步伐 ,不能实现理想中的制度演变     

BALANCED ARRAYS AND WEIGHING DESIGNS

Dey (19711, Saha (1975), Kageyama & Saha (1983) and others have shown how optimum chemical balance weighing designs can be constructed from the incidence matrices of balanced incomplete block (BIB) designs. In this paper, it is shown that weighing designs can be constructed from some suitably chosen two-symbol balanced arrays of strength two, which need not always be incidence matrices of BIB designs. The findings lead us to construct new optimum chemical balance weighing designs from incidence matrices of BIB designs.