The trigonometry of matrix statistics

被引：8
|
作者：
Gustafson, Karl [1 ]
机构：
[1] Univ Colorado, Dept Math, Boulder, CO 80309 USA
来源：
INTERNATIONAL STATISTICAL REVIEW | 2006年 / 74卷 / 02期
关键词：
operator trigonometry; antieigenvalue; antieigenvector; parameter estimation; Watson statistical efficiency; canonical correlation; Rayleigh-Ritz theory;
D O I：
10.1111/j.1751-5823.2006.tb00169.x
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
A matrix trigonometry developed chiefly by this author during the past 40 years has interesting applications to certain situations in statistics. The key conceptual entity in this matrix trigonometry is the matrix (maximal) turning angle. Associated entities (originally so-named by this author) are the matrix antieigenvalues and corresponding antieigenvectors upon which the matrix obtains its critical turning angles. Because this trigonometry is the natural one for linear operators and matrices, it also is the natural one for matrix statistics.
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页码：187 / 202
页数：16
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