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The Foundations of Finite Sample Estimation in Stochastic Processes

V. P. Godambe
Biometrika
Vol. 72, No. 2 (Aug., 1985), pp. 419-428
Published by: Oxford University Press on behalf of Biometrika Trust
DOI: 10.2307/2336094
Stable URL: http://www.jstor.org/stable/2336094
Page Count: 10
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The Foundations of Finite Sample Estimation in Stochastic Processes
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Abstract

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.

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