Abstract
The linear regression model, with carriers treated random, has been defined through 2.4(36)–2.4(40):
By Theorem 2.4.6, the model is, at every θ∈ℝk, L2 differentiable with L2 derivative and Fisher information of full rank given by
Thus the robustness results for general parameter apply with this ideal center model. Due to the regression structure, however, additional variants of neighborhoods, bias terms, and corresponding optimization (and, in principle, construction) problems arise.
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© 1994 Springer-Verlag New York, Inc.
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Rieder, H. (1994). Robust Regression. In: Robust Asymptotic Statistics. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4684-0624-5_7
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DOI: https://doi.org/10.1007/978-1-4684-0624-5_7
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