Research output: Contribution to journal › Article › peer-review
Constructing initial estimators in one-step estimation procedures of nonlinear regression. / Linke, Yu Yu; Borisov, I. S.
In: Statistics and Probability Letters, Vol. 120, 01.01.2017, p. 87-94.Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - Constructing initial estimators in one-step estimation procedures of nonlinear regression
AU - Linke, Yu Yu
AU - Borisov, I. S.
N1 - Publisher Copyright: © 2016 Elsevier B.V.
PY - 2017/1/1
Y1 - 2017/1/1
N2 - We discuss an approach to construct explicitly calculable consistent estimators for parameters of some nonlinear regression models. The estimators of such a kind can be used as initial estimators in one-step estimation procedures for unknown parameters of these models.
AB - We discuss an approach to construct explicitly calculable consistent estimators for parameters of some nonlinear regression models. The estimators of such a kind can be used as initial estimators in one-step estimation procedures for unknown parameters of these models.
KW - Asymptotic normality
KW - Initial estimator
KW - Nonlinear regression
KW - One-step M-estimator
KW - α-consistency
KW - LINEAR-REGRESSION
KW - alpha(n)-consistency
UR - http://www.scopus.com/inward/record.url?scp=84992522070&partnerID=8YFLogxK
U2 - 10.1016/j.spl.2016.09.022
DO - 10.1016/j.spl.2016.09.022
M3 - Article
AN - SCOPUS:84992522070
VL - 120
SP - 87
EP - 94
JO - Statistics and Probability Letters
JF - Statistics and Probability Letters
SN - 0167-7152
ER -
ID: 9056112