关于加权广义逆的三个矩阵乘积的不变性

利用矩阵D-AXC的最大最小秩,给出了矩阵AXC的乘积、秩以及值域的不变性,其中X为矩阵B的各种加权广义逆.     

（0，1）—矩阵类U（R，S）的势函数

讨论了（０，１）—矩阵类Ｕ（Ｒ，Ｓ）中所含指定的行和向量Ｒ＝（ｒ１，ｒ２，…，ｒｍ），列和向量Ｓ＝（ｓ１，ｓ２；，…，ｓｎ）的（０，１）—矩阵的势ｆｍ，ｎ（Ｒ，Ｓ），给出了求ｆｍ，ｎ（Ｒ，Ｓ）的递归公式．     

Methods to Explore Uncertainty and Bias Introduced by Job Exposure Matrices

Job exposure matrices (JEMs) are used to measure exposures based on information about particular jobs and tasks. JEMs are especially useful when individual exposure data cannot be obtained. Nonetheless, there may be other workplace exposures associated with the study disease that are not measured in available JEMs. When these exposures are also associated with the exposures measured in the JEM, biases due to uncontrolled confounding will be introduced. Furthermore, individual exposures differ from JEM measurements due to differences in job conditions and worker practices. Uncertainty may also be present at the assessor level since exposure information for each job may be imprecise or incomplete. Assigning individuals a fixed exposure determined by the JEM ignores these uncertainty sources. We examine the uncertainty displayed by bias analyses in a study of occupational electric shocks, occupational magnetic fields, and amyotrophic lateral sclerosis.     

关于Fan Ky不等式的推广

利用积分方法和矩阵理论研究了正定对称矩阵的行列式不等式,考虑了可逆矩阵的行列式不等式,得到了Fan Ky不等式的若干推广;应用Gram的正定性,给出了Fan Ky不等式的一个改进.     

A Correlation Test for Normality Based on the Lévy Characterization

A powerful test of fit for normal distributions is proposed. Based on the Lévy characterization, the test statistic is the sample correlation coefficient of normal quantiles and sums of pairs of observations from a random sample. Since the test statistic is location-scale invariant, critical values can be obtained by simulation without estimating any parameters. It is proved that this test is consistent. A power comparison study including some directed tests shows that the proposed test is competitive, it is more powerful than the well-known Jarque–Bera test, and it is comparable to Shapiro–Wilk test against a number of alternatives.     

Wilks’ factorization of the matrix-variate Dirichlet–Riesz distributions

The Riesz distributions on positive definite symmetric matrices are used to introduce a class of Dirichlet–Riesz distributions. In addition, several distributional properties are stated. Essentially, we show the relationship between the Dirichlet–Riesz distributions of the first kind and the second kind, respectively. We derive Wilks’ factorization of the matrix-variate Dirichlet–Riesz. Further, several results on the product of Riesz and beta–Riesz matrices with a set of Dirichlet–Riesz matrices of the first kind have been derived.     

Nearly optimal covariate designs—Part I

We propose to discuss at length several examples from standard text books. All of these examples deal with analysis of covariance (ANCOVA) models and related analyses of data. We intend to capitalize on our understanding of optimal covariate designs (OCDs) in different ANCOVA models and re-visit these examples with a view to suggest optimal/nearly optimal designs for estimation of the covariate parameter(s). As we will see, for some examples our task is very much routine but for others, it is indeed a highly non trivial exercise.

?We intent to cover a total of six examples—divided in two parts. This is Part I—dealing with two examples.     

可对称化矩阵特征值的任意扰动

针对可对称化矩阵,研究了可对称化矩阵特征值的任意扰动和实任意扰动。从Schur分解入手,利用矩阵可对角化的性质,通过矩阵等式的恒等变形,得到了可对角化矩阵关于F-范数和Q-范数的任意扰动界。     

一些特殊的n阶方阵的基本性质

初步研究了次转置矩阵、次对称矩阵和次单位矩阵的基本性质.     

Portfolio optimization: New capabilities and future methods

Summary  This paper addresses the problem of portfolio selection in finance. In many cases, currently available software to compute the efficient frontier runs into difficulty in problems with more than about 600 securities. To proceed beyond this size, it is often necessary to modify the problem in which case there is typically a loss of information. In this paper, we discuss a computer capability that can exactly compute mean-variance efficient frontiers of problems with up to 2,000 securities in very reasonable time (even if a problem’s covariance matrix is 100% dense). The paper also discusses an augmentation to the theory of portfolio selection that allows multiple objectives (such as dividends, liquidity, social responsibility, amount invested in R&D, and so forth) to be incorporated into the portfolio selection process. In such problems, the efficient set is no longer a “frontier,” but is now best described as a “surface” with the interesting property that it is composed of platelets (like on the back of a turtle). Moreover, the computer capability that can compute the exact efficient frontier of a mean-variance problem with up to 2,000 securities also has, after additional coding, the ability to compute exactly all platelets of the efficient surface of a tri-criterion portfolio problem with up to 400 securities.

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Zusammenfassung  In dieser Arbeit stellen wir einen leistungsf?higen Rechenalgorithmus vor, um den effizienten Rand (die nichtdominierten Alternativen) von Portfolio-Auswahlproblemen in der Finanzierung zu bestimmen. Wir bezeichnen den Berechnungsalgorithmus, der in Java programmiert ist, mit MPQ (multi-parametric quadratic programming). MPQ weist gegenüber bisherigen Berechnungsverfahren eine Reihe von Vorteilen auf: Es kann für umfangreiche Anwendungsf?lle genutzt werden, ist durch passable Rechenzeiten charakterisiert und kann die Menge effizienter Alternativen in einem Bruchteil bisher üblicher Rechenzeiten bestimmen.