Geodesic
Admissibility of the estimate of least squares. Unusual property of the normal law
Matematičeskie zametki, Tome 6 (1969) no. 1, pp. 81-89 Cet article a éte moissonné depuis la source Math-Net.Ru

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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. 
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     author = {A. M. Kagan and O. V. Shalaevskii},
     title = {Admissibility of the estimate of least squares. {Unusual} property of the normal law},
     journal = {Matemati\v{c}eskie zametki},
     pages = {81--89},
     year = {1969},
     volume = {6},
     number = {1},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/MZM_1969_6_1_a9/}
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A. M. Kagan; O. V. Shalaevskii. Admissibility of the estimate of least squares. Unusual property of the normal law. Matematičeskie zametki, Tome 6 (1969) no. 1, pp. 81-89. http://geodesic.mathdoc.fr/item/MZM_1969_6_1_a9/