Statistical Proofs of Some Matrix Theorems
Radhakrishna Rao, C.
Internat. Statist. Rev., Tome 74 (2006) no. 1, p. 169-185 / Harvested from Project Euclid
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.
Publié le : 2006-08-14
Classification:  Cauchy-Schwarz inequality,  Fisher information,  Kronecker product,  Milne's inequality,  Parallel sum of matrices,  Schur product
@article{1153748791,
     author = {Radhakrishna Rao, C.},
     title = {Statistical Proofs of Some Matrix Theorems},
     journal = {Internat. Statist. Rev.},
     volume = {74},
     number = {1},
     year = {2006},
     pages = { 169-185},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1153748791}
}
Radhakrishna Rao, C. Statistical Proofs of Some Matrix Theorems. Internat. Statist. Rev., Tome 74 (2006) no. 1, pp.  169-185. http://gdmltest.u-ga.fr/item/1153748791/