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On equivalence problem in linear regression models. II. Unbiased estimation of the covariance matrix scalar factor
Applications of Mathematics, Tome 25 (1980) no. 6, pp. 423-431
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There exist many different ways of determining the best linear unbiased estimation of regression coefficients in general regression model. In Part I of this article it is shown that all these ways are numerically equivalent almost everyvhere. In Part II conditions are considered under which all the unbiased estimations of the unknown covariance matrix scalar factor are numerically equivalent almost everywhere.
There exist many different ways of determining the best linear unbiased estimation of regression coefficients in general regression model. In Part I of this article it is shown that all these ways are numerically equivalent almost everyvhere. In Part II conditions are considered under which all the unbiased estimations of the unknown covariance matrix scalar factor are numerically equivalent almost everywhere.
DOI : 10.21136/AM.1980.103881
Classification : 62J05, 65C99
Keywords: control; numerical stability; best linear unbiased estimation; unknown covariance matrix scalar factor 
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Wimmer, Gejza. On equivalence problem in linear regression models. II. Unbiased estimation of the covariance matrix scalar factor. Applications of Mathematics, Tome 25 (1980) no. 6, pp. 423-431. doi: 10.21136/AM.1980.103881

[1] C. R. Rao: Unified Theory of Linear Estimation. Sankhyā, Vol. 33 1971, pp. 371 - 394. | MR | Zbl

[2] C. R. Rao: Linear Statistical Inference and Its Applications. John Wiley, N. York 1973. | MR | Zbl

[3] C. R. Rao S. K. Mitra: Generalized Inversa of Matrices and Its Applications. John Wiley, N. York 1971. | MR

[4] C. R. Rao: Corrigenda. Sankhyā A, Vol. 34 1972 p. 477. | MR | Zbl

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