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Article

Keywords:
multivariate model; linear hypothesis; variance components; insensitive region
Summary:
In regular multivariate regression model a test of linear hypothesis is dependent on a structure and a knowledge of the covariance matrix. Several tests procedures are given for the cases that the covariance matrix is either totally unknown, or partially unknown (variance components), or totally known.
References:
[1] Anderson T. W.: Introduction to Multivariate Statistical Analysis. Wiley, New York 1958 MR 0091588 | Zbl 1039.62044
[2] Kubáček L., Kubáčková, L., Volaufová J.: Statistical Models with Linear Structures. Veda (Publishing House of Slovak Academy of Sciences), Bratislava 1995
[3] Lešanská E.: Optimization of the size of nonsensitiveness regions. Appl. Math. 47 (2002), 9–23 MR 1876489
[4] Rao C. R.: Linear Statistical Inference and Its Applications. Second edition. Wiley, New York 1973 MR 0346957 | Zbl 0256.62002
[5] Rao C. R., Kleffe J.: Estimation of Variance Components and Applications. North–Holland, Amsterdam 1988 MR 0933559 | Zbl 0645.62073
[6] Rao C. R., Mitra S. K.: Generalized Inverse of Matrices and Its Applications. Wiley, New York 1971 MR 0338013 | Zbl 0261.62051
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