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The Foundations of Finite Sample Estimation in Stochastic Processes
V. P. Godambe
Vol. 72, No. 2 (Aug., 1985), pp. 419-428
Stable URL: http://www.jstor.org/stable/2336094
Page Count: 10
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The Gauss-Markov theorem on least squares for linear models derives its general applicability because it depends on the underlying distribution only through the first two moments. In this paper, a similar theorem is established within the context of stochastic processes. Various problems of finite sample estimation are solved by application of this theorem.
Biometrika © 1985 Biometrika Trust