Convergence systems and strong consistency of least squares estimates in regression models
A recent theorem of T. L. Hai, H. Robbins, and C. Z. Wei (J. Multivariate Anal. 9 (1979), 343-362) is extended to a more general form which unifies previous results in the literature on the strong consistency of least squares estimates in multiple regression models with nonrandom regressors. In particular the issue of strong consistency of the least squares estimate in the Gauss-Markov model, in the i.i.d. model with infinite second moment, and in general time series models is examined. In this connection, some basic properties of convergence systems are also obtained and are applied to the strong consistency problem.
Year of publication: |
1981
|
---|---|
Authors: | Gui-Jing, Chen ; Lai, T. L. ; Wei, C. Z. |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 11.1981, 3, p. 319-333
|
Publisher: |
Elsevier |
Keywords: | Convergence system multiple regression strong consistency Gauss-Markov model martingale difference sequence linear process |
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