重新表述克里斯托夫定理冗长而复杂的证明:附带一些新发现的教程

Haruhiko Ogasawara
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引用次数: 0

摘要

克里斯托夫定理给出了某些矩阵乘积迹的全局最大值和最小值,而无需使用微积分或拉格朗日乘法器,在心理测量学和多元分析中有着广泛的应用。然而,尽管该定理在实践中应用广泛,但却一直未得到充分利用。部分原因可能是该定理的证明过程冗长而复杂。在本教程中,将重新表述或提供一些已知或新的公理,以便理解证明中的要点。然后,展示了使用父正交矩阵的修正克利斯朵夫定理和ten Berge定理,这可能有助于了解克利斯朵夫定理和ten Berge定理的性质。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rephrasing the Lengthy and Involved Proof of Kristof’s Theorem: A Tutorial with Some New Findings
Kristof’s theorem gives the global maximum and minimum of the trace of some matrix products without using calculus or Lagrange multipliers with various applications in psychometrics and multivariate analysis. However, the underutilization has been seen irrespective of its great use in practice. This may partially be due to the lengthy and involved proof of the theorem. In this tutorial, some known or new lemmas are rephrased or provided to understand the essential points in the proof. ten Berge’s generalized Kristof theorem is also addressed. Then, the modified Kristof and ten Berge theorems using parent orthonormal matrices are shown, which may be of use to see the properties of the Kristof and ten Berge theorems.  
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