用修正重标极差法对上证指数长期记忆性的研究

本文以上证指数周收益率为研究对象,分别采用重标极差分析法和修正重标极差分析法,通过计算V统计量的值对其进行长期记忆性的检验。由于不能排除V统计量的值存在超出上侧分位点的可能性,本文进行了双侧检验,并分析了R/S分析法产生偏差的原因。得出上证指数周收益率时间序列并未表现出显著的长期记忆性的结论。     

带参数估计的极差控制图设计

现实中,过程参数常常未知,需由第Ⅰ阶段的受控样本数据估计得到.不同的第Ⅰ阶段样本数据集对应着目标参数的不同估计值,进而会导致不同的控制限与不同的控制图表现.对于某位实际工作人员而言,最可能的情况是他手里仅有一组第Ⅰ阶段数据集,因此研究在给定一组第Ⅰ阶段数据集下控制图的表现,即条件表现,更具实际意义.基于Monter Carlo模拟,研究了基于样本平均极差,样本平均标准差和样本合并标准差等3种参数估计形式下常见的等尾极差图和无偏极差图的条件平均链长分布,结果表明参数估计对控制图影响严重.为了弥补第Ⅰ阶段数据量的不足,基于bootstrap方法,提出了修正控制图以获得理想的条件受控表现.比较结果显示,基于样本合并标准差的估计方法更好,修正的无偏极差图表现优于相应的修正等尾极差图.     

非对称极差控制图研究

本文针对现有的国家标准极差控制图的一些问题,在极差的统计性质的基础上,提出了非对称极差控制图的想法,并构造了三种不同的非对称极差控制图,分别给出了报警率达到0.27%时的上、下控制限系数,使得它们的控制限计算非常简便易行.本文给出了这三种非对称极差控制图的含义和各自的侧重点,并将它们与国家标准的极差控制图在对应检验的势函数以及平均运行长度两个方面进行了比较.使用这三种非对称极差控制图可以使真实报警率达到0.27%,远小于现有的国家标准极差控制图的真实报警率.无偏控制图由于具有了"无偏"这一优良性质,成为三张非对称控制图中最具吸引力的.     

全变化参数的中位值-极差联合控制图的经济设计

在统计质量控制中,通常利用中位值图和极差图来控制生产过程的均值和方差.建立了全变化参数的中位值和极差联合控制图,同时提出了一种费用函数以提供最优化设计参数的方法,最后通过一个例子说明了该模型能节约成本.     

小批量生产的质量控制图

本文介绍Q统计量,并以样本极差代替方差,给出极差的Q控制图。     

基于带隐含波动率的混频条件自回归极差模型的股市波动率预测研究

极值理论表明价格极差是波动率的一个有效的估计量。同时,众多研究表明,基于期权价格的隐含波动率包含了市场前瞻性的信息。本文在经典的基于极差的条件自回归极差(CARR)模型基础上,充分考虑价格极差的长期动态性以及期权隐含波动率包含的信息,构建了带隐含波动率的混频CARR (CARR-MIDAS-IV)模型对极差波动率进行建模和预测。CARR-MIDAS-IV模型通过引入MIDAS结构能够捕获条件极差的长期趋势过程(长期记忆特征)。而且,CARRMIDAS-IV模型同时考虑了极值信息以及隐含波动率包含的关于未来波动率的信息(前瞻信息)对波动率建模和预测。采用恒生指数和标普500指数及其隐含波动率数据进行的实证研究表明,充分考虑条件极差的长记忆性(MIDAS结构)以及隐含波动率包含的信息对于极差波动率建模和预测具有重要作用。总体而言,本文构建的CARR-MIDAS-IV模型相比其他许多竞争模型具有更为优越的数据拟合效果以及波动率预测能力。特别地,CARR-MIDAS-IV模型对于中、高波动期波动率的预测具有较强的稳健性。     

条件自回归极差模型的渐近性质

在误差项独立同分布的条件下，本文讨论了条件自回归极差模型条件解和无条件解的渐近性质．利用随机游动的极限性质得到了条件解收敛于无条件解的充分条件，任意阶矩有限的充要条件以及外生变量与内生变量持续性的充要条件．所得到的结论适用于已得到应用的平稳条件自回归极差模型，也适用于包含单位根的模型和满足条件的其他类型的非平稳过程，为模型的统计推断提供了理论基础．     

关于指数分布无失效数据的Bayes分析的注记

本文对指数分布无失效数据，在修正似然函数的基础上，给出了Ｂａｙｅｓ分析的方法，并与［１］中结果进行了比较，同时修正了［２］中的错误．     

定时截尾下指数分布的修正最大似然估计

本文在定时截尾情形下对指数分布提出了修正的最大似然估计，且把修正方法应用到定时截尾恒加试验和步加试验，模拟结果表明修正后的估计量的均方误差有了明显减少。     

基于半极差模型的高低价预测

在局部动态的几何布朗运动框架下,本文探讨了提出的半极差与资产价格波动率的理论关系,并将文献中几种主要的动态波动率模型统一地转化为等价的半极差模型,由此能够直接给出高低价的预测结果。通过对沪深300股指期货上市以来的日度极值数据进行实证分析,本文揭示出半极差(或高低价)具有较强的可预测性,并且合理地利用开盘价信息以及充分考虑长记忆特征有助于提高模型的拟合预测能力。     

A new approach with orthogonal array for global optimization in design of experiments

In this paper, we develop an approach that determines the overall best parameter setting in design of experiments. The approach starts with successive orthogonal array experiments and ends with a full factorial experiment. The setup for the next orthogonal-array experiment is obtained from the previous one by either fixing a factor at a given level or by reducing the number of levels considered for all currently non-fixed factors. We illustrate this method using an industrial problem with seven parameters, each with three levels. In previous work, the full factorial of 3⁷ = 2,187 points was evaluated and the best point was found. With the new method, we found the same point using 3% of these evaluations. As a further comparison, we obtained the optimum using a traditional Taguchi approach, and found it corresponded to the 366th of the 2,187 possibilities when sorted by the objective function. We conclude the proposed approach would provide an accurate, fast, and economic tool for optimization using design of experiments.     

Generating and improving orthogonal designs by using mixed integer programming

Analysts faced with conducting experiments involving quantitative factors have a variety of potential designs in their portfolio. However, in many experimental settings involving discrete-valued factors (particularly if the factors do not all have the same number of levels), none of these designs are suitable.In this paper, we present a mixed integer programming (MIP) method that is suitable for constructing orthogonal designs, or improving existing orthogonal arrays, for experiments involving quantitative factors with limited numbers of levels of interest. Our formulation makes use of a novel linearization of the correlation calculation.The orthogonal designs we construct do not satisfy the definition of an orthogonal array, so we do not advocate their use for qualitative factors. However, they do allow analysts to study, without sacrificing balance or orthogonality, a greater number of quantitative factors than it is possible to do with orthogonal arrays which have the same number of runs.     

八行设计平均冒尖性的比较

本文通过计算机验证，比较了八行三列、四列不同结构的正交设计和均匀设计的平均冒尖性，利用差值评分给出了它们的平均冒尖性的比较结果。     

Gradient Estimation Schemes for Noisy Functions

In this paper, we analyze different schemes for obtaining gradient estimates when the underlying functions are noisy. Good gradient estimation is important e.g. for nonlinear programming solvers. As error criterion, we take the norm of the difference between the real and estimated gradients. The total error can be split into a deterministic error and a stochastic error. For three finite-difference schemes and two design of experiments (DoE) schemes, we analyze both the deterministic errors and stochastic errors. We derive also optimal stepsizes for each scheme, such that the total error is minimized. Some of the schemes have the nice property that this stepsize minimizes also the variance of the error. Based on these results, we show that, to obtain good gradient estimates for noisy functions, it is worthwhile to use DoE schemes. We recommend to implement such schemes in NLP solvers.We thank our colleague Jack Kleijnen for useful remarks on an earlier version of this paper and Gül Gürkan for providing us with relevant literature. Moreover, we thank the anonymous referee for valuable remarks.     

Customized sequential designs for random simulation experiments: Kriging metamodeling and bootstrapping

This paper proposes a novel method to select an experimental design for interpolation in random simulation, especially discrete event simulation. (Though the paper focuses on Kriging, this design approach may also apply to other types of metamodels such as non-linear regression models and splines.) Assuming that simulation requires much computer time, it is important to select a design with a small number of observations (or simulation runs). The proposed method is therefore sequential. Its novelty is that it accounts for the specific input/output behavior (or response function) of the particular simulation at hand; i.e., the method is customized or application-driven. A tool for this customization is bootstrapping, which enables the estimation of the variances of predictions for inputs not yet simulated. The method is tested through two classic simulation models, namely the expected steady-state waiting time of the M/M/1 queuing model, and the mean costs of a terminating (s, S) inventory simulation. For these two simulation models the novel design indeed gives better results than a popular alternative design, namely Latin Hypercube Sampling (LHS) with a prefixed sample.     

外表设计及其案例研究（Ⅱ）

本篇前部分介绍参数设计的一些案例，这些案例被用来对外表设计诸方法进行实际考核和比较；后部分介绍对外表设计诸方法进行比较所采用的一些准则及其有关问题．     

Factor screening for simulation with multiple responses: Sequential bifurcation

The goal of factor screening is to find the really important inputs (factors) among the many inputs that may be changed in a realistic simulation experiment. A specific method is sequential bifurcation (SB), which is a sequential method that changes groups of inputs simultaneously. SB is most efficient and effective if the following assumptions are satisfied: (i) second-order polynomials are adequate approximations of the input/output functions implied by the simulation model; (ii) the signs of all first-order effects are known; and (iii) if two inputs have no important first-order effects, then they have no important second-order effects either (heredity property). This paper examines SB for random simulation with multiple responses (outputs), called multi-response SB (MSB). This MSB selects groups of inputs such that—within a group—all inputs have the same sign for a specific type of output, so no cancellation of first-order effects occurs. To obtain enough replicates (replications) for correctly classifying a group effect or an individual effect as being important or unimportant, MSB applies Wald’s sequential probability ratio test (SPRT). The initial number of replicates in this SPRT is also selected efficiently by MSB. Moreover, MSB includes a procedure to validate the three assumptions of MSB. The paper evaluates the performance of MSB through extensive Monte Carlo experiments that satisfy all MSB assumptions, and through a case study representing a logistic system in China; the results are very promising.     

An Evolutionary Approach for the Design and Scheduling of Electroplating Facilities

This paper tackles the Cyclic Hoists Scheduling Problem. This problem is often encountered in electroplating facilities when mass production is required. Then a repetitive sequence of moves is searched for the hoists. We more precisely deal with a global optimization problem that simultaneously considers the design and the scheduling of such production lines. It consists in studying systems integrating several transportation resources, called hoists, by minimizing the cycle time, while minimizing the number of hoists used. To achieve these goals, we use an evolutionary approach. The encoding of one solution is based on the representation of the empty moves of the hoists. To evaluate each individual, we propose a linear programming model. This one both verifies the satisfaction of constraints and provides the best cycle time for the considered number of hoists. This contribution describes a promising approach to solving a simple version of this problem, namely cyclic hoist scheduling, based on Evolutionary Algorithms (EAs), which is an optimization method inspired by biological evolution models. The issues of solution encoding and specialised genetic operators with a repair procedure of the infeasible solutions are discussed. Some results are presented with benchmark examples.      

A travel-time model for a person-onboard order picking system

The design of an order picking system in a distribution center depends on several decisions, where a key decision is determining the optimal storage system configuration (the number, length, and height of the storage aisles). To make this decision, a throughput model that considers vertical, as well as horizontal, travel is needed. In this paper we extend prior research that considers horizontal travel for a given number and length of the storage aisles so that we are also able to consider the height of the aisles as well. Such a model will provide a more accurate estimate of the throughput of an order picker and it will also permit an examination of the tradeoff between the length and height of the aisles. The analytical model we develop to estimate throughput is based on probability models and order statistics results assuming random storage. It is intended for person-onboard order picking systems and we consider both Tchebychev and rectilinear travel. We illustrate the use of our travel-time model by incorporating it into a simple, cost-based optimization model to recommend the height of a one-pallet-deep storage system.     

An Algorithmic Framework for the Exact Solution of the Prize-Collecting Steiner Tree Problem

The Prize-Collecting Steiner Tree Problem (PCST) on a graph with edge costs and vertex profits asks for a subtree minimizing the sum of the total cost of all edges in the subtree plus the total profit of all vertices not contained in the subtree. PCST appears frequently in the design of utility networks where profit generating customers and the network connecting them have to be chosen in the most profitable way. Our main contribution is the formulation and implementation of a branch-and-cut algorithm based on a directed graph model where we combine several state-of-the-art methods previously used for the Steiner tree problem. Our method outperforms the previously published results on the standard benchmark set of problems. We can solve all benchmark instances from the literature to optimality, including some of them for which the optimum was not known. Compared to a recent algorithm by Lucena and Resende, our new method is faster by more than two orders of magnitude. We also introduce a new class of more challenging instances and present computational results for them. Finally, for a set of large-scale real-world instances arising in the design of fiber optic networks, we also obtain optimal solution values. Received: April, 2004 This work has been partly supported by the RTNADONET, 504438, by the Doctoral Scholarship Program of the Austrian Academy of Sciences (DOC) and by CNR and MIUR, Italy.A preliminary version of this paper appeared as [21].