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August 2006 Statistical Proofs of Some Matrix Theorems
C. Radhakrishna Rao
Internat. Statist. Rev. 74(2): 169-185 (August 2006).


Books on linear models and multivariate analysis generally include a chapter on matrix algebra, quite rightly so, as matrix results are used in the discussion of statistical methods in these areas. During recent years a number of papers have appeared where statistical results derived without the use of matrix theorems have been used to prove some matrix results which are used to generate other statistical results. This may have some pedagogical value. It is not, however, suggested that prior knowledge of matrix theory is not necessary for studying statistics. It is intended to show that a judicious use of statistical and matrix results might be of help in providing elegant proofs of problems both in statistics and matrix algebra and make the study of both the subjects somewhat interesting. Some basic notions of vector spaces and matrices are, however, necessary and these are outlined in the introduction to this paper.


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C. Radhakrishna Rao. "Statistical Proofs of Some Matrix Theorems." Internat. Statist. Rev. 74 (2) 169 - 185, August 2006.


Published: August 2006
First available in Project Euclid: 24 July 2006

Keywords: Cauchy-Schwarz inequality , Fisher information , Kronecker product , Milne's inequality , Parallel sum of matrices , Schur product

Rights: Copyright © 2006 International Statistical Institute


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Vol.74 • No. 2 • August 2006
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