Geodesic
On the ith Latent Root of a Complex Matrix(1)
Canadian mathematical bulletin, Tome 15 (1972) no. 3, pp. 323-327

Voir la notice de l'article provenant de la source Cambridge University Press

Goodman [1] has pointed out the applications of the distributional results of the complex multivariate normal statistical analysis. Khatri [4], has suggested the maximum latent root statistic for testing the reality of a covariance matrix. The joint distribution of the latent roots under certain null hypotheses can be written as, [2], [3], 1 where and 
Al-Ani, Sabri. On the ith Latent Root of a Complex Matrix(1). Canadian mathematical bulletin, Tome 15 (1972) no. 3, pp. 323-327. doi: 10.4153/CMB-1972-059-x
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[1] 1. Goodman, N. R., Statistical analysis based on a certain multivariate complex Gaussion distribution (an introduction), Ann. Math. Stat. 34, (1963), 152-176. Google Scholar

[2] 2. Khatri, C. G., Distribution of the largest or the smallest root under null hypotheses concerning complex multivariate normal, Ann. Math. Statist. 35 (1964), 1807-1810. Google Scholar

[3] 3. Khatri, C. G., Classical statistical analysis based on a certain multivariate complex Gaussion distribution, Ann. Math. Statist. 36, (1965), 98-114. Google Scholar

[4] 4. Khatri, C. G.,A test for reality of a covariance matrix in certain complex Gaussion distribution, Ann. Math. Statist. 36, (1965), 115-119. Google Scholar

[5] 5. Pillai, K. C. S., and Dotson, C., Power comparisons of tests of two multivariate hypotheses based on individual characteristic roots, Mimeo. Series No. 108, Dept. of Statist., Purdue University, 1967. Google Scholar

[6] 6. Roy, S. N., Some aspects of multivariate analysis, Wiley, New York, 1958. Google Scholar

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