Rates of convergence in the asymptotic normality for some local maximum estimators
Asymptotic normality of estimators defined by maximizing a random criterion function is considered. Assuming smooth stochastic differentiability (stronger than the Hoffmann-Jørgensen stochastic differentiability) of the criterion function the author derives the rate of convergence in a general result on asymptotic normality of local maximum estimators. Examples and applications of the results, including Huber's \(M\)-estimate, are given.
scientific article; zbMATH DE number 1059800