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A new estimation procedure for a partially nonlinear model via a mixed‐effects approach
Author(s) -
Li Runze,
Nie Lei
Publication year - 2007
Publication title -
canadian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 51
eISSN - 1708-945X
pISSN - 0319-5724
DOI - 10.1002/cjs.5550350305
Subject(s) - nonlinear system , mathematics , component (thermodynamics) , parametric statistics , gaussian , semiparametric model , nonlinear regression , estimation , nonparametric statistics , econometrics , mathematical optimization , computer science , statistics , regression analysis , physics , thermodynamics , management , quantum mechanics , economics
The authors consider the estimation of the parametric component of a partially nonlinear semiparametric regression model whose nonparametric component is viewed as a nuisance parameter. They show how estimation can proceed through a nonlinear mixed‐effects model approach. They prove that under certain regularity conditions, the proposed estimate is consistent and asymptotically Gaussian. They investigate its finite‐sample properties through simulations and illustrate its use with data on the relation between the photosynthetically active radiation and the net ecosystem‐atmosphere exchange of carbon dioxide.