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Admissibility of the estimate of least squares. Unusual property of the normal law
A. M. Kagan, O. V. Shalaevskii Leningrad Department of V. A. Steklov Institute of Mathematics, USSR Academy of Sciences
Abstract:
It is shown that in the linear-regression scheme, the estimates of the squares of parametric vector-functions are admissible in the class of unbiased estimates if and only if the observations obey a normal law. Here, the covariation matrix (non-negative definite) serves as a measure of the quality of the estimate.
Received: 01.11.1968
Citation:
A. M. Kagan, O. V. Shalaevskii, “Admissibility of the estimate of least squares. Unusual property of the normal law”, Mat. Zametki, 6:1 (1969), 81–89; Math. Notes, 6:1 (1969), 508–512
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https://www.mathnet.ru/eng/mzm6900 https://www.mathnet.ru/eng/mzm/v6/i1/p81
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Abstract page: | 271 | Full-text PDF : | 112 | First page: | 1 |
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