Geodesic
Sufficient conditions for the strong consistency of least squares estimator with α-stable errors
Discussiones Mathematicae. Probability and Statistics, Tome 27 (2007) no. 1-2, pp. 27-45.

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Let Y_i = x_i^Tβ + e_i, 1 ≤ i ≤ n, n ≥ 1 be a linear regression model and suppose that the random errors e₁, e₂, ... are independent and α-stable. In this paper, we obtain sufficient conditions for the strong consistency of the least squares estimator β̃ of β under additional assumptions on the non-random sequence x₁, x₂,... of real vectors.
Keywords: linear models, least squares estimator, strong consistency, stability 
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Mexia, João; da Silva, João. Sufficient conditions for the strong consistency of least squares estimator with α-stable errors. Discussiones Mathematicae. Probability and Statistics, Tome 27 (2007) no. 1-2, pp. 27-45. http://geodesic.mathdoc.fr/item/DMPS_2007_27_1-2_a2/

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