统计中的线性代数和多元分析:二十世纪的发展和相互联系

IF 0.6 Q3 MATHEMATICS
N. Bingham, W. Krzanowski
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引用次数: 3

摘要

线性代数和矩阵代数与统计学之间最明显的联系是在多元分析领域。我们回顾了在上个世纪两者的发展过程中,通过研究一些关键领域来相互影响的方式。我们从矩阵和线性代数开始,它在19世纪出现,并最终在20世纪渗透到本科课程中。我们继续对统计学中的多变量分析进行类似的解释。我们认为1936年有三个关键的发展,战后初期还有三个。然后我们会用到一些我们需要的线性代数的特殊结果。我们简要讨论了其中的四个主要贡献者,并以13个“案例研究”结束,在一系列具体案例中展示了这些一般代数方法是如何被很好地利用并改变了统计的面貌。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Linear algebra and multivariate analysis in statistics: development and interconnections in the twentieth century
The most obvious points of contact between linear and matrix algebra and statistics are in the area of multivariate analysis. We review the way that, as both developed during the last century, the two influenced each other by examining a number of key areas. We begin with matrix and linear algebra, its emergence in the nineteenth century, and its eventual penetration into the undergraduate curriculum in the twentieth century. We continue with a similar account for multivariate analysis in statistics. We pick out the year 1936 for three key developments, and the early post-war period for three more. We then turn to some special results in linear algebra that we need. We briefly discuss four of the main contributors, and close with thirteen ‘case studies’, showing in a range of specific cases how these general algebraic methods have been put to good use and changed the face of statistics.
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来源期刊
British Journal for the History of Mathematics
British Journal for the History of Mathematics Arts and Humanities-History and Philosophy of Science
CiteScore
0.50
自引率
0.00%
发文量
22
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