Ӧ�ø���ͳ�� 2012, 28(3) 285-300 DOI:      ISSN: 1001-4268 CN: 31-1256

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Partial Linear Models for Longitudinal Data Based on Penalized General Method of Moments
Ni Yanfeng, Zhu Zhongyi
Department of Statistics, Management School of Fudan University
Abstract:

For the analysis of partial linear model
with longitudinal data, the general procedure is to fit the
nonparametric part with kernel or spline estimation, followed by
generalized linear model estimating frame. In this paper, we fit the
nonparametric part with P-spline, and estimate the parametrical and
nonparametric part with different Generalized method of moments
estimation for different moment conditions, implemented by the proof
of the asymptotical properties for the estimator, which is also been
proved by simulation and illustrative example, from which we can
also find out that different penalized general method of moments
estimations for different moment conditions perform more
efficiently.

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