@article{4b917aa710e14e978d5450028ceb21c4,
title = "Constructing explicit estimators in nonlinear regression problems",
abstract = "In the paper, we propose a general approach to constructing explicit consistent estimators for some classes of nonlinear regression models. These estimators can be used as initial ones in one-step estimation procedures capable of delivering, in a sense, optimal estimators in an explicit form.",
keywords = "Asymptotic normality, Explicit estimator, Initial estimator, Nonlinear regression, One-step estimator, α -consistency",
author = "Linke, {Yu Yu} and Borisov, {I. S.}",
note = "Funding Information: ∗Received by the editors February 24, 2016. This work was partially supported by the Russian Foundation for Basic Research (grant 18-01-00074). Originally published in the Russian journal Teoriya Veroyatnostei i ee Primeneniya, 63 (2018), pp. 29–56. http://www.siam.org/journals/tvp/63-1/T98889.html †Sobolev Institute of Mathematics, Novosibirsk, Russia, and Novosibirsk State University, Novosibirsk, Russia (linke@math.nsc.ru, sibam@math.nsc.ru)",
year = "2018",
month = jan,
day = "1",
doi = "10.1137/S0040585X97T988897",
language = "English",
volume = "63",
pages = "22--44",
journal = "Theory of Probability and its Applications",
issn = "0040-585X",
publisher = "SIAM PUBLICATIONS",
number = "1",
}