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Robust Strongly Convergent M-Estimators Under Non-IID Assumption

Published 24 Oct 2021 in math.ST, math.FA, math.PR, stat.ME, and stat.TH | (2110.12526v1)

Abstract: M-estimators for Generalized Linear Models are considered under minimal assumptions. Under these preliminaries, strong convergence of the estimators are discussed and an expansion of the estimating operators are given in the non-i.i.d. case with the i.i.d. case shown as a particular application. Various consequences of the results are discussed for binary and continuous models.

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