基于多维矩阵项目组织在某国防项目中的应用

按照型号国防项目管理的要求,在某大型国防项目管理实践中项目组织形式组建进行了探讨。本文首先分析当前各种项目管理组织形式特点,在分析本单位实际情况的基础上,针对型号国防项目管理的特殊需求,提出了一种多维矩阵的项目组织,并就该组织机构在运行中出现的一些问题进行了分析,探讨了该种组织形式的优缺点,提出了进一步的改进问题的办法和措施。     

蕴含在函数矩阵中的积分不等式

以平均值不等式为基础,获得正值连续函数矩阵中的一个积分不等式公式,利用此公式,布涅可夫斯基(V.J.Buniakowski)等积分不等式可通过构作矩阵进行直观明了的证明;利用此公式,对所有的正值连续函数矩阵可构造出相应的积分不等式.     

人口预测的随机方法:基于Leslie矩阵和ARMA模型

本文探讨了人口预测的一种随机方法。文章回顾了经典的Leslie矩阵并结合中国的人口统计数据,用时间序列的ARMA模型对未来的生育率、死亡率进行估计,并由此构造Les-lie矩阵,经时间序列的数据中心化,根据自相关函数、偏自相关函数的截尾性或拖尾性,以及贝叶斯信息准则函数方法对模型定阶,实现对ARMA模型的识别。在中国人口预测方面的应用证明,基于Leslie矩阵和ARMA模型的人口随机预测方法是稳健的,具有很强的适用性。由于统计数据可获得性的局限,对模型做了不少假设和近似。随着人口数据的积累,未来将会在此方面有所改进。     

一类扩展的投入产出模型

 内容提要：基于居民部门封闭的投入产出模型进行扩展,并将政府部门从最终需求列中转移出来,纳入到生产部门,列入投入产出表的第Ⅰ象限,政府部门所在的行是以货币形式表现的各部门（包括居民部门）的税收支付,政府部门所在的列是政府对各个部门的各种消费品和劳务的消费额,得到了扩展的局部闭投入产出模型,并在此模型的基础上得到了各种乘数。进一步将投资考虑进去得到动态投入产出扩展模型,使得国民经济各个生产部门、居民部门、政府部门成为一个完整的投入产出平衡体。     

Some families of group divisible designs

Generalizing methods of constructions of Hadamard group divisible designs due to Bush (1979), some new families of semi-regular or regular group divisible designs are produced. Furthermore, new nonisomorphic solutions for some known group divisible designs are given, together with useful group divisible designs not listed in Clatworthy (1973).     

On the norm of alias matrices in balanced fractional 2m factorial designs of resolution 2l + 1

The norm $\text{6A6 = {tr(A′A)}}{}^{\mathrm{<mtext>1</mtext><mtext>2</mtext>}}$ of the alias matrix A of a design can be used as a measure for selecting a design. In this paper, an explicit expression for 6A6 will be given for a balanced fractional 2^m factorial design of resolution 2l + 1 which obtained from a simple array with parameters (m; λ₀, λ₁,…, λ_m). This array is identical with a balanced array of strength m, m constraints and index set {λ₀, λ₁,…, λ_m}. In the class of the designs of resolution V (l = 2) obtained from S-arrays, ones which minimize 6A6 will be presented for any fixed N assemblies satisfying (i) m = 4, 11 ? N ? 16, (ii) m = 5, 16 ? N ? 32, and (iii) m = 6, 22 ? N ? 40.     

Variance least squares estimators for multivariate linear mixed model

Non-iterative, distribution-free, and unbiased estimators of variance components by least squares method are derived for multivariate linear mixed model. A general inter-cluster variance matrix, a same-member only general inter-response variance matrix, and an uncorrelated intra-cluster error structure for each response are assumed. Projection method is suggested when unbiased estimators of variance components are not nonnegative definite matrices. A simulation study is conducted to investigate the properties of the proposed estimators in terms of bias and mean square error with comparison to the Gaussian (restricted) maximum likelihood estimators. The proposed estimators are illustrated by an application of gene expression familial study.     

Optimal two treatment repeated measurement designs for three periods

Repeated Measurement Designs, with two treatments, n (experimental) units and p periods are examined, the two treatments are denoted A and B. The model with independent observations within and between treatment sequences is used. Optimal designs are derived for: (i) the difference of direct treatment effects and the difference of residual effects, (ii) the difference of direct treatment effects, and (iii) the difference of residual effects. We prove that for three periods when n is odd the optimal design in the three cases (i), (ii), and (iii) is determined by taking the sequences BAA and ABB in numbers differing by one. If n is even, the optimal design in cases (i), (ii), and (iii) is again the same, by taking the sequences ABB and BAA in equal numbers. In case (i), for n even or odd, in the optimal design there is no correlation between the two estimated parameters. For n even, case (i) was solved by Cheng and Wu in 1980. The above imply that with two treatments in practice are preferable to use three periods instead of two.     

基于Gabor变换和灰度梯度共生矩阵的人耳识别研究

人耳识别作为一种新兴的生物特征识别技术,具有其自身独特的优势。提出一种基于Gabor变换和灰度梯度共生矩阵的人耳身份识别方法。首先,利用Gabor变换和灰度-梯度共生矩阵融合提取人耳图像的纹理特征,然后采用K-NN分类器对特征进行分类。该方法用USTB人耳图像库做测试。实验结果表明介绍的提取人耳图像的纹理融合特征的方法优于只采用Gabor变换提取特征或是只提取灰度梯度共生矩阵的二次统计特征的性能。在明氏距离测度及K=1时,交叉验证识别率达到81.77%。     

Fully modified estimation of cointegrating vectors via var prewhitening: A simulation study

Summary In this paper we investigate, by simulation methods, the finite samples properties of the Fully Modified Least Squares (FMLS) estimator of cointegrating vectors when the long run covariance matrix is estimated via VAR prewhitening. We compare this estimator to the FMLS estimator based on an automatic or a fixed bandwidth kernel estimator of the long run covariance matrix. By and large, FMLS estimator based on VAR prewhitening perform better than FMLS based on fixed bandwidth or automatic bandwidth, with the latter behaving almost in the same way in finite samples. More importantly, the empirical distribution of a Wald test statistic built from VAR prewhitened FMLS is closer to the asymptoticχ ² distribution than those obtained from alternative kernel estimators. Thus, our findings strongly favor the use of VAR prewhitening in the FM correction of the OLS estimator. We would like to thank P. C. B. Phillips for his suggestions, two anonymous referees for detailed comments, and the participants of the IGIER (Milan), the University of Padova and the CIDE (Bologna) seminars for comments. This paper has been presented at the Econometric Society European Meeting 1984 held at Maastricht, Netherlands. We acknowledge financial support from MURST-Funds 40%. The usual disclaimers apply.