ASYMPTOTIC PROPERTIES OF ONE-STEP WEIGHTED M-ESTIMATORS WITH APPLICATIONS TO REGRESSION

作者：Linke Yu Yu^*

来源：Theory of Probability and Its Applications, 2018, 62(3): 373-398.

DOI：10.1137/S0040585X97T988691

• one-step M-estimators
• one-step weighted M-estimators
• M-estimators
• asymptotic normality
• Newton's iteration method
• initial estimator
• nonlinear regression

We study the asymptotic behavior of one-step weighted M-estimators based on independent not necessarily identically distributed observations, which approximate consistent weighted M-estimators. We find sufficient conditions for asymptotic normality of these estimators. As an application, we consider some known regression models where the one-step estimation under consideration allows us to construct explicit asymptotically optimal estimators having the same accuracy as the least-squares or quasi-likelihood estimators.

• 出版日期2018