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Asymptotic properties of one-step weighted $M$-estimators and applications to some regression problems by Linke, Yu. Yu. is a scholarly article available to read on EtoBox.

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We study asymptotic behavior of one-step weighted $M$-estimators based on samples from arrays of not necessarily identically distributed random variables and representing explicit approximations to the corresponding consistent weighted $M$-estimators. Sufficient conditions are presented for asymptotic normality of the one-step weighted $M$-estimators under consideration. As a consequence, we consider some well-known nonlinear regression models where the procedure mentioned allow us to construct explicit asymptotically optimal estimators.

Author

Linke, Yu. Yu.

Published

2015

Language

EN