基于计算机试验的均匀设计

本文在计算机试验的基础上，提出了最小相关准则和最小距离离差准则，并将信息论中的Hamming距离和Lee距离引入到计算机试验中，证明了均匀设计在Hamming距离下的最优性和部分好格子点均匀设计在Lee距离下的最优性．基于偏差的考虑，给出了一类新的好格子点均匀设计和一个学习算法，利用这个学习算法，给出了基于Lee距离的最小距离离差准则的均匀设计表的构造方法．通过与已有的好格子点均匀设计和循环拉丁方均匀设计作比较，证明了文中的均匀设计在距离和偏差意义下有更好的均匀性．     

混水平均匀设计的构造

我们用离散偏差来度量部分因子设计的均匀性,本文的目的在于寻找一些构造混水平均匀设计的方法,这些方法比文献中已有的方法更简单且计算成本更低.我们得到了离散偏差的一个下界,如果一个U 型设计的离散偏差值达到这个下界,那么该设计是—个均匀设计.我们建立了均匀设计与组合设计理论中一致可分解设计之间的联系.通过一致可分解设计,我们提出了一些构造均匀设计的新方法,同时也给出了许多均匀设计存在的无穷类.     

Wrap-Around L2-Discrepancy of Random Sampling, Latin Hypercube and Uniform Designs

For comparing random designs and Latin hypercube designs, this paper con- siders a wrap-around version of the L₂-discrepancy (WD). The theoretical expectation and variance of this discrepancy are derived for these two designs. The expectation and variance of Latin hypercube designs are significantly lower than those of the corresponding random designs. We also study construction of the uniform design under the WD and show that one-dimensional uniform design under this discrepancy can be any set of equidistant points. For high dimensional uniform designs we apply the threshold accepting heuristic for finding low discrepancy designs. We also show that the conjecture proposed by K. T. Fang, D. K. J. Lin, P. Winker, and Y. Zhang (2000, Technometrics) is true under the WD when the design is complete.     

Lower bounds and stochastic optimization algorithms for uniform designs with three or four levels

New lower bounds for three- and four-level designs under the centered -discrepancy are provided. We describe necessary conditions for the existence of a uniform design meeting these lower bounds. We consider several modifications of two stochastic optimization algorithms for the problem of finding uniform or close to uniform designs under the centered -discrepancy. Besides the threshold accepting algorithm, we introduce an algorithm named balance-pursuit heuristic. This algorithm uses some combinatorial properties of inner structures required for a uniform design. Using the best specifications of these algorithms we obtain many designs whose discrepancy is lower than those obtained in previous works, as well as many new low-discrepancy designs with fairly large scale. Moreover, some of these designs meet the lower bound, i.e., are uniform designs.

     

低偏差OALHD的构造

本文给出了利用均匀设计和正交表构造低偏差OALH设计的方法，该方法构造的设计既有优良的均匀性具有正交设计的均衡性，一个更重要的优点是可以构造较大样本容量的设计点集，本文同时给出了某些参数的均匀设计表，这些设计优于现有的均匀设计，具有实用价值。     

可卷型L_2-偏差的水平置换方法构造混合水平设计

提出了一种通过置换因子的水平来构造具有较小可卷型L_2-偏差的混合水平均匀设计的新方法.首先建立了混合水平设计的平均可卷型L_2-偏差与广义字长型的定量关系,并以具有较小广义字长型的混合水平设计为初始设计,对其作水平置换,计算其可卷型L_2-偏差,找到具有最小的可卷型L_2-偏差的设计就是相对较好的设计.为了使算法更加有效,还运用了可卷型L_2-偏差的两个性质.数值结果显示通过这种方法构造的设计在可卷型L_2-偏差下表现良好.     

Some results on resolvable incomplete block designs

This paper is concerned with the uniformity of a certain kind of resolvable incomplete block (RIB for simplicity) design which is called the PRIB design here. A sufficient and necessary condition is obtained, under which a PRIB design is the most uniform in the sense of a discrete discrepancy measure, and the uniform PRIB design is shown to be connected. A construction method for such designs via a kind of U-type designs is proposed, and an existence result of these designs is given. This method sets up an important bridge between PRIB designs and U-type designs.     

混料试验的D—最优对称设计,算法及应用

本文着重研究了混料试验的D—最优对称设计.基于Fedorov及Atwood的迭代方法,作者给出一个构造D—最优对称设计的改进算法.这个新算法由双循环迭代构成:从初始设计中减去最小方差对称点的设计测度;增加设计测度于最大方差的对称设计点,同时,本算法还只在对称子区域中寻找最大方差设计点,这样就使得Fedorov算法的收敛速度有了显著地提高,并能构造出更高效的D—最优对称设计.另外还给出一些构造实例.     

An efficient method for constructing uniform designs with large size

Many construction methods for (nearly) uniform designs have been proposed under the centered $L_2$ -discrepancy, and most of them are only suitable for constructing designs with small size. This paper proposes a new method, called mixture method (MM), to construct nearly symmetrical/asymmetrical uniform designs with large number of runs and/or large number of factors. The new method has the “better than given” property, i.e., the resulting design is better than existing designs in the sense of the pre-decided criterion. Moreover, the computational speed of MM is faster than most existing methods.     

Application of minimum projection uniformity criterion in complementary designs for q-level factorials

We study the complementary design problem, which is to express the uniformity pattern of a q-level design in terms of that of its complementary design. Here, a pair of complementary designs form a design in which all the Hamming distances of any two distinct runs are the same, and the uniformity pattern proposed by H. Qin, Z. Wang, and K. Chatterjee [J. Statist. Plann. Inference, 2012, 142: 1170–1177] comes from discrete discrepancy for q-level designs. Based on relationships of the uniformity pattern between a pair of complementary designs, we propose a minimum projection uniformity rule to assess and compare q-level factorials.     

Uniform supersaturated design and its construction

Supersaturated designs are factorial designs in which the number of main effects is greater than the number of experimental runs. In this paper, a discrete discrepancy is proposed as a measure of uniformity for supersaturated designs, and a lower bound of this discrepancy is obtained as a benchmark of design uniformity. A construction method for uniform supersaturated designs via resolvable balanced incomplete block designs is also presented along with the investigation of properties of the resulting designs. The construction method shows a strong link between these two different kinds of designs     

Geometric isomorphism check for symmetric factorial designs

Two designs are geometrically isomorphic if one design can be obtained from the other by reordering the runs, relabeling the factors and/or reversing the level order of one or more factors. In this paper, some new necessary and sufficient conditions for identifying geometric isomorphism of symmetric designs with prime levels are provided. A new algorithm for checking geometric isomorphism is proposed and a searching result for geometrically non-isomorphic 3-level orthogonal arrays of 18 runs is presented.     

Centered -discrepancy of random sampling and Latin hypercube design, and construction of uniform designs

In this paper properties and construction of designs under a centered version of the -discrepancy are analyzed. The theoretic expectation and variance of this discrepancy are derived for random designs and Latin hypercube designs. The expectation and variance of Latin hypercube designs are significantly lower than that of random designs. While in dimension one the unique uniform design is also a set of equidistant points, low-discrepancy designs in higher dimension have to be generated by explicit optimization. Optimization is performed using the threshold accepting heuristic which produces low discrepancy designs compared to theoretic expectation and variance.

     

Constructions of uniform designs by using resolvable packings and coverings

Uniform designs have been widely used in computer experiments, as well as in industrial experiments when the underlying model is unknown. Based on the discrete discrepancy, the link between uniform designs, and resolvable packings and coverings in combinatorial theory is developed. Through resolvable packings and coverings without identical parallel classes, many infinite classes of new uniform designs are then produced.     

Optimum mechanism for breaking the confounding effects of mixed-level designs

Fractional factorial designs (FFD’s) are no doubt the most widely used designs in the experimental investigations due to their efficient use of experimental runs to study many factors simultaneously. One consequence of using FFD’s is the aliasing of factorial effects. Follow-up experiments may be needed to break the confounding. A simple strategy is to add a foldover of the initial design, the new fraction is called a foldover design. Combining a foldover design with the original design converts a design of resolution r into a combined design of resolution \(r+1\). In this paper, we take the centered \(L_2\)-discrepancy \(({\mathcal {CD}})\) as the optimality measure to construct the optimal combined design and take asymmetrical factorials with mixed two and three levels, which are most commonly used in practice, as the original designs. New and efficient analytical expressions based on the row distance of the \({\mathcal {CD}}\) for combined designs are obtained. Based on these new formulations, we present new and efficient lower bounds of the \({\mathcal {CD}}\). Using the new formulations and lower bounds as the benchmarks, we may implement a new algorithm for constructing optimal mixed-level combined designs. By this search heuristic, we may obtain mixed-level combined designs with low discrepancy.     

混水平列扩充设计的均匀性

在许多工业应用中,通常分步应用跟随设计来考察输入(因子)和产出(响应)间的关系.在许多跟随设计中,在跟随阶段可以加入一些另外的两水平或三水平因子,因为它们在初始阶段可能被忽略但又十分重要.文章在均匀性准则下,提出了中心化L2-偏差意义下的混水平列扩充均匀设计,给出了列扩充设计在中心化L2-偏差下的解析表达式及相应的下界,其可作为搜索均匀设计的基准.进一步,具有一个附加区组因子的列扩充设计是均匀的当且仅当未加区组因子时的列扩充设计是均匀的.     

Minimum secondary aberration fractional factorial split-plot designs in terms of consulting designs

It is very powerful for constructing nearly saturated factorial designs to characterize fractional factorial (FF) designs through their consulting designs when the consulting designs are small. Mukerjee and Fang employed the projective geometry theory to find the secondary wordlength pattern of a regular symmetrical fractional factorial split-plot (FFSP) design in terms of its complementary subset, but not in a unified form. In this paper, based on the connection between factorial design theory and coding theory, we obtain some general and unified combinatorial identities that relate the secondary wordlength pattern of a regular symmetrical or mixed-level FFSP design to that of its consulting design. According to these identities, we further establish some general and unified rules for identifying minimum secondary aberration, symmetrical or mixed-level, FFSP designs through their consulting designs.     

模糊互补判断矩阵一致性改进的新途径

针对模糊互补判断矩阵的一致性修正问题,本文从模糊一致矩阵传统定义出发,深入挖掘了一致性定义中所涉及到的三元素组之间的关系,在给出相关定理的基础上,提出了一种改善模糊互补判断矩阵一致性的新算法,从理论上分析了该算法的可行性,并利用模拟仿真的方法给出了与本算法相关的几种比较分析。     

Multiplicative designs I: The normal and reducible cases

Multiplicative designs, square designs with a rank one intersection pattern, are investigated. In particular we determine all designs for which some incidence matrix is reducible and we show if some incidence matrix is normal the design must be uniform with three families of exceptions. Some new designs are constructed.     

投影均匀分片拉丁超立方体设计

空间填充设计是有效的计算机试验设计,比如均匀设计、最大最小距离拉丁超立方体设计等.虽然这些设计在整个试验空间中有较好的均匀性,但其低维投影均匀性可能并不理想.对于因子是定量的计算机试验,已有文献构造了诸如最大投影设计、均匀投影设计等相适应的设计;而对于同时含有定性因子和定量因子的计算机试验,尚未有投影均匀设计的相关文献.文章提出了综合投影均匀准则,利用门限接受算法构造了投影均匀的分片拉丁超立方体设计.在新构造设计中,整体设计与每一片设计均具有良好的投影均匀性.模拟结果显示,与随机分片拉丁超立方体设计相比,利用新构造设计进行试验而拟合的高斯过程模型具有更小的均方根预测误差.