圆的面积公式的新证明——验证圆的面积公式S=πr^2

本文应用阿基米德的内外正多边形逼近法和开普勒的无穷分割法,站在后人的肩膀上,运用极限理论,洛比达法则,以及收敛法则,夹逼法则,三角函数等近代数学的办法,来为开普勒对上述问题做个解释,从而验证圆的面积计算公式确实为S=πr^2     

基于原型逼近法的招标代理机构转化业主需求机理

为了使编制的招标文件真实地反映业主的需求,提高招标文件的编制质量,促进招标代理机构自身业务水平的提升,利用原型逼近的方法,设计出项目需求的转化机理,确定项目初始需求、还原逼近真实需求,并在招标文件的编写中予以体现,达到业主需求的最终转化目的。     

模糊概率决策系统的属性约简

基于模糊等价关系及论域上的概率分布建立模糊概率信息系统,并给出了模糊概率信息系统的熵与条件熵.最后基于模糊概率信息系统的条件熵提出模糊概率决策信息系统的属性约简并给出了算法.     

独立逆抽样下优势比的置信区间

本文对独立逆抽样设计下优势比的置信区间的构造进行了研究,包括三个已有的方法,以及本文引入的鞍点逼近方法。通过模拟比较了这四个方法给出的置信区间。模拟结果表明,基于鞍点逼近方法给出的置信区间不比另外三种方法差。并且在一些情况下表现还优于其它三个方法。     

Between stability and higher-order asymptotics

We discuss the effects of model misspecifications on higher-order asymptotic approximations of the distribution of estimators and test statistics. In particular we show that small deviations from the model can wipe out the nominal improvements of the accuracy obtained at the model by second-order approximations of the distribution of classical statistics. Although there is no guarantee that the first-order robustness properties of robust estimators and tests will carry over to second-order in a neighbourhood of the model, the behaviour of robust procedures in terms of second-order accuracy is generally more stable and reliable than that of their classical counterparts. Finally, we discuss some related work on robust adjustments of the profile likelihood and outline the role of computer algebra in this type of research.     

Symbolic computation for approximating distributions of some families of one and two-sample nonparametric test statistics

A conditional saddlepoint approximation was provided by Gatto and Jammalamadaka (1999) for computing the distribution function of many test statistics based on dependent quantities like multinomial frequencies, spacing frequencies, etc. The considerable complexity of the formulas involved can be bypassed by symbolic computation. This article illustrates the effectiveness of symbolic computation to evaluate the saddlepoint approximation for the likelihood ratio, the exponential score, and the Wald-Wolfowitz test statistics. The case of composite hypotheses is also discussed.     

Statistical Analysis of Marginal Count Failure Data

Manufacturers want to assess the quality andreliability of their products. Specifically, they want to knowthe exact number of failures from the sales transacted duringa particular month. Information available today is sometimesincomplete as many companies analyze their failure data simplycomparing sales for a total month from a particular departmentwith the total number of claims registered for that given month.This information—called marginal count data—is, thus,incomplete as it does not give the exact number of failures ofthe specific products that were sold in a particular month. Inthis paper we discuss nonparametric estimation of the mean numbersof failures for repairable products and the failure probabilitiesfor nonrepairable products. We present a nonhomogeneous Poissonprocess model for repairable products and a multinomial modeland its Poisson approximation for nonrepairable products. A numericalexample is given and a simulation is carried out to evaluatethe proposed methods of estimating failure probabilities undera number of possible situations.     

Approximation Algorithms for the Multiple Knapsack Problem with Assignment Restrictions

Motivated by a real world application, we study the multiple knapsack problem with assignment restrictions (MKAR). We are given a set of items, each with a positive real weight, and a set of knapsacks, each with a positive real capacity. In addition, for each item a set of knapsacks that can hold that item is specified. In a feasible assignment of items to knapsacks, each item is assigned to at most one knapsack, assignment restrictions are satisfied, and knapsack capacities are not exceeded. We consider the objectives of maximizing assigned weight and minimizing utilized capacity.We focus on obtaining approximate solutions in polynomial computational time. We show that simple greedy approaches yield 1/3-approximation algorithms for the objective of maximizing assigned weight. We give two different 1/2-approximation algorithms: the first one solves single knapsack problems successively and the second one is based on rounding the LP relaxation solution. For the bicriteria problem of minimizing utilized capacity subject to a minimum requirement on assigned weight, we give an (1/3,2)-approximation algorithm.