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A general asymptotic theory of \(M\)-estimators. II. (English) Zbl 1185.62053
Summary: This second part of the paper presents conditions for asymptotic normality of \(M\)-estimators of parameters of general statistical models with independent observations. They extend the conditions for \(\sqrt{n}\)-consistency established in the previous part in Math. Methods Stat. 12, No. 4, 454–477 (2004). Applications to the estimation of parameters of linear and nonlinear regression are used to demonstrate that these conditions lead in special models to new results which are comparable and sometimes stronger than those formerly established in the papers dealing directly with these models.

62F12 Asymptotic properties of parametric estimators
62F35 Robustness and adaptive procedures (parametric inference)
62J02 General nonlinear regression
62J05 Linear regression; mixed models