NDLI: Efficient estimation of longitudinal data additive varying coefficient regression models

Content Provider	Springer Nature Link
Author	Liu, Shu
Copyright Year	2017
Abstract	We consider a longitudinal data additive varying coefficient regression model, in which the coefficients of some factors (covariates) are additive functions of other factors, so that the interactions between different factors can be taken into account effectively. By considering within-subject correlation among repeated measurements over time and additive structure, we propose a feasible weighted two-stage local quasi-likelihood estimation. In the first stage, we construct initial estimators of the additive component functions by B-spline series approximation. With the initial estimators, we transform the additive varying coefficients regression model into a varying coefficients regression model and further apply the local weighted quasi-likelihood method to estimate the varying coefficient functions in the second stage. The resulting second stage estimators are computationally expedient and intuitively appealing. They also have the advantages of higher asymptotic efficiency than those neglecting the correlation structure, and an oracle property in the sense that the asymptotic property of each additive component is the same as if the other components were known with certainty. Simulation studies are conducted to demonstrate finite sample behaviors of the proposed estimators, and a real data example is given to illustrate the usefulness of the proposed methodology.
Ending Page	550
Page Count	22
Starting Page	529
File Format	PDF
ISSN	01689673
e-ISSN	16183932
Journal	Acta Mathematicae Applicatae Sinica
Issue Number	2
Volume Number	33
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2017-04-08
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	additive vary-coefficient model Asymptotic properties of estimators within-subject correlation Asymptotic properties Estimation Theoretical, Mathematical and Computational Physics Nonparametric regression Applications of Mathematics Math Applications in Computer Science longitudinal data modified Cholesky decomposition
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics

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