Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
Toward the Notion of Intrinsically Linear Models in Nonlinear Regression. / Linke, Yu Yu; Borisov, I. S.
в: Siberian Advances in Mathematics, Том 29, № 3, 01.07.2019, стр. 210-216.Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
}
TY - JOUR
T1 - Toward the Notion of Intrinsically Linear Models in Nonlinear Regression
AU - Linke, Yu Yu
AU - Borisov, I. S.
N1 - Publisher Copyright: © 2019, Allerton Press, Inc.
PY - 2019/7/1
Y1 - 2019/7/1
N2 - We discuss a refinement of the notion of intrinsical linearity of nonlinear regression models. We show that some known nonlinear regression models satisfy this definition. This fact allows us to find the shortest way to construct consistent (or asymptotically normal) estimators for the parameters of such models. Moreover, we show that one of the known previous interpretations of this notion may lead to inconsistent estimation procedures.
AB - We discuss a refinement of the notion of intrinsical linearity of nonlinear regression models. We show that some known nonlinear regression models satisfy this definition. This fact allows us to find the shortest way to construct consistent (or asymptotically normal) estimators for the parameters of such models. Moreover, we show that one of the known previous interpretations of this notion may lead to inconsistent estimation procedures.
KW - explicit estimator
KW - intrinsically linear model
KW - nonlinear regression
UR - http://www.scopus.com/inward/record.url?scp=85071618647&partnerID=8YFLogxK
U2 - 10.3103/S1055134419030064
DO - 10.3103/S1055134419030064
M3 - Article
AN - SCOPUS:85071618647
VL - 29
SP - 210
EP - 216
JO - Siberian Advances in Mathematics
JF - Siberian Advances in Mathematics
SN - 1055-1344
IS - 3
ER -
ID: 21472316