Abstract
Some sufficient conditions to establish the rate of convergence of certain M-estimators in a Gaussian white noise model are presented They are applied to some concrete problems including jump point estimation and nonparametric maximum likelihood estimation for the regression function The results are shown by means of a maximal inequality
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