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Keywords:
control; numerical stability; best linear unbiased estimation; unknown covariance matrix scalar factor
control; numerical stability; best linear unbiased estimation; unknown covariance matrix scalar factor
Summary:
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.
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References:
[1] C. R. Rao: Unified Theory of Linear Estimation. Sankhyā, Vol. 33 1971, pp. 371 - 394. MR 0319321 | Zbl 0236.62048
[2] C. R. Rao: Linear Statistical Inference and Its Applications. John Wiley, N. York 1973. MR 0346957 | Zbl 0256.62002
[3] C. R. Rao S. K. Mitra: Generalized Inversa of Matrices and Its Applications. John Wiley, N. York 1971. MR 0338013
[4] C. R. Rao: Corrigenda. Sankhyā A, Vol. 34 1972 p. 477. MR 0347011 | Zbl 0261.62051
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