Strong consistency of least-squares estimates in regression models

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Strong consistency of least-squares estimates in regression models.

A general theorem on the limiting behavior of certain weighted sums of i.i.d. random variables is obtained. This theorem is then applied to prove the strong consistency of least-squares estimates in linear and nonlinear regression models with i.i.d. errors under minimal assumptions on the design and weak moment conditions on the errors.

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ژورنال

عنوان ژورنال: Proceedings of the National Academy of Sciences

سال: 1977

ISSN: 0027-8424,1091-6490

DOI: 10.1073/pnas.74.7.2667