两变量随机截距模型的最优设计

本文考虑两变量随机截距模型在单位正方形设计域上的D-,G-,A-,Ds-和I-最优设计.证明了最优设计在设计区域的顶点处获得,得到了几类不依赖于随机截距项的最优设计模拟结果表明最优设计较随机设计可大幅提高参数估计的精确性.     

Panel Data模型基于Within估计的最优设计

本文研究二元Panel Data模型基于Within估计在恒等设计类中的D-,A-,I-和E-最优设计.文章首先证明了二元Panel Data模型基于Within估计在恒等设计类中的几类最优设计可在设计域的顶点处获得;研究发现模型的D-,A-和E-最优设计均为设计域顶点上的等权重设计,I-最优设计为对称设计;结果还表明等权重设计具有较高的I-效.     

均衡稳健性与有效性的设计

均匀设计和最优设计是两类重要的设计类型,各有优缺点.本文考虑门限接受法构造多维的确定性D-最优设计,然后结合均匀设计与D-最优设计而给出一种构造设计的方法,模拟结果显示该构造方法所构造的设计可以有效地均衡稳健性和有效性.     

关于离散型试验的最优设计

本文对线性模型中离散型试验的设计阵提出了一致最优与分组E最优的标准,找到了一致最优设计阵存在的充要条件,证明了正交设计与BIB区组设计是分组E最优设计和E最优设计.本文中的方法可以用于非离散型的试验,得到相应的结果.     

混料模型的混合最优设计

最优设计是试验设计中必不可少的一种设计方法,混合最优设计是二步最优设计中一种常见的应用。本文以混料模型为基础,提出一种新的寻求混合最优设计的方法,并以此方法解决了混料模型的混合最优设计问题。     

含过程变量的K模型最优正交区组设计

混料试验设计是研究混合物成份比例的试验设计,最优设计则是混料试验设计中重要的研究方向,其中以D-最优设计应用最为广泛.文中对K模型混料试验与最优准则进行介绍,对其含过程变量的3分量二阶K模型给出满足D-最优准则的正交区组设计,最后推广至q分量情形并证明.     

四水平计算机试验设计的构造

编码理论在最优设计的构造中已被广泛应用.本文通过修正Gray映射编码变换来构造用于计算机试验的四水平均匀设计,其效率通过离散偏差进行刻画;同时也给出了离散偏差的下界,这个下界可作为获得最优设计的一个基准.     

基于形状优化框架下的Steklov特征值问题研究

<正>1引言特征值问题在应用数学分支和工程中,尤其是在最优设计问题中,有很多的应用,所以特征值问题的最优化已经有了较为深入的研究,见在我们的研究当中,最优设计问题常常以一种指定载荷的设计下、能量的极小化问题的形式出现.在大多数关于最优设计的文章里面,我们更重视在一个固定载荷下条件下结构的最     

最优设计

随着优选法群众性的推广和应用的深人,以及我国电子计算技术的迅速发展,一些单位已将优选法和其它最优化方法应用到工程设计和科学研究工作中(简称最优设计).最近两、三年,最优设计在我国日益受到重视,应用范围日益增多,同时使用的方法也有改进和发展.特别是有不少最优设计问题的解决是和电子计算机的使用分不开的.利用电子计算机来进行数字的试验,可以使得有些实物试验次数减少,设计周期缩短.这对于不可     

多响应Scheffé混料模型最优设计

在工业生产及科学实验中经常需要对多个混料试验指标进行统计分析,由于各响应指标之间存在一定的相关性,关于这类模型下最优设计的构造就变得比较复杂.本文在特定的相关条件下,构造了p维响应二阶Scheffe模型的D-最优设计,并讨论了二响应Scheffe模型的Ds-最优设计与A-最优设计.这三种最优设计的柱点测度只与变量个数有关而与响应协方差无关.     

Global Optimization Problems in Optimal Design of Experiments in Regression Models

In this paper we show that optimal design of experiments, a specific topic in statistics, constitutes a challenging application field for global optimization. This paper shows how various structures in optimal design of experiments problems determine the structure of corresponding challenging global optimization problems. Three different kinds of experimental designs are discussed: discrete designs, exact designs and replicationfree designs. Finding optimal designs for these three concepts involves different optimization problems.     

Construction of supersaturated design with large number of factors by the complementary design method

Supersaturated designs (SSDs) have been widely used in factor screening experiments. The present paper aims to prove that the maximal balanced designs are a kind of special optimal SSDs under the E(f _NOD) criterion. We also propose a new method, called the complementary design method, for constructing E(f _NOD) optimal SSDs. The basic principle of this method is that for any existing E(f _NOD) optimal SSD whose E(fNOD) value reaches its lower bound, its complementary design in the corresponding maximal balanced design is also E(f _NOD) optimal. This method applies to both symmetrical and asymmetrical (mixed-level) cases. It provides a convenient and efficient way to construct many new designs with relatively large numbers of factors. Some newly constructed designs are given as examples.     

An effective algorithm for generation of factorial designs with generalized minimum aberration

Fractional factorial designs are popular and widely used for industrial experiments. Generalized minimum aberration is an important criterion recently proposed for both regular and non-regular designs. This paper provides a formal optimization treatment on optimal designs with generalized minimum aberration. New lower bounds and optimality results are developed for resolution-III designs. Based on these results, an effective computer search algorithm is provided for sub-design selection, and new optimal designs are reported.     

Minimum Ellipsiod and Optim alDesign

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Construction of optimal supersaturated designs by the packing method

A supersaturated design is essentially a factorial design with the equal occurrence of levels property and no fully aliased factors in which the number of main effects is greater than the number of runs. It has received much recent interest because of its potential in factor screening experiments. A packing design is an important object in combinatorial design theory. In this paper, a strong link between the two apparently unrelated kinds of designs is shown. Several criteria for comparing supersaturated designs are proposed, their properties and connections with other existing criteria are discussed. A combinatorial approach, called the packing method, for constructing optimal supersaturated designs is presented, and properties of the resulting designs are also investigated. Comparisons between the new designs and other existing designs are given, which show that our construction method and the newly constructed designs have good properties.     

Optimal and near-optimal mixed covering arrays by column expansion

This paper describes constructions for strength-2 mixed covering arrays developed from index-1 orthogonal arrays, ordered designs and covering arrays. The constructed arrays have optimal or near-optimal sizes. Conditions for achieving optimal size are described. An optimization among the different ingredient arrays to maximize the number of factors of each alphabet size is also presented.     

Some Results on Two-stage Clinical Trials

Among a variety of adaptive designs, stage-wise design, especially, two-stage design is an important one because patient responses are not available immediately but are available in batches or in termittently insome situations. In this paper, by Bayesian method, the general formula of asymptotical optimal worth is given,meanwhile the length of some optimal designs at first stage concerning two-stage trials in several important cases has been obtained.     

A-optimal designs for an additive cubic model

Chan et al. (1998a) obtained A-optimal designs for an additive quadratic mixture model for q≥3 mixture components. In this paper, we obtain the A-optimal designs for an additive cubic model for q≥3 mixture components using the class of symmetric weighted centroid designs based on barycentres of various depths. We observe that barycentres of depths 0 and 2 are possible support points for an A-optimal design. We have also given the optimal weights of A-optimal designs for 3≤q≤17.     

An algorithmic approach to finding factorial designs with generalized minimum aberration

Factorial designs are arguably the most widely used designs in scientific investigations. Generalized minimum aberration (GMA) and uniformity are two important criteria for evaluating both regular and non-regular designs. The generation of GMA designs is a non-trivial problem due to the sequential optimization nature of the criterion. Based on an analytical expression between the generalized wordlength pattern and a uniformity measure, this paper converts the generation of GMA designs to a constrained optimization problem, and provides effective algorithms for solving this particular problem. Moreover, many new designs with GMA or near-GMA are reported, which are also (nearly) optimal under the uniformity measure.