FPCA-based estimation for generalized functional partially linear models
FPCA-based estimation for generalized functional partially linear models
复制标题
基于 FPCA 的广义函数部分线性模型估计
DOI:
10.1007/s00362-018-01066-8
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发表时间:
2019-01
影响因子:
1.3
通讯作者:
Tianfa Xie
中科院分区:
文献类型:
--
作者:
Ruiyuan Cao;Jiang Du;Jianjun Zhou;Tianfa Xie
In real data analysis, practitioners frequently come across the case that a discrete response will be related to both a function-valued random variable and a vector-value random variable as the predictor variables. In this paper, we consider the generalized functional partially linear models (GFPLM). The infinite slope function in the GFPLM is estimated by the principal component basis function approximations. Then, we consider the theoretical properties of the estimator obtained by maximizing the quasi likelihood function. The asymptotic normality of the estimator of the finite dimensional parameter and the rate of convergence of the estimator of the infinite dimensional slope function are established, respectively. We investigate the finite sample properties of the estimation procedure via Monte Carlo simulation studies and a real data analysis.
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DOI:
10.1198/tas.2003.s212
发表时间:
2003-02
期刊:
The American Statistician
影响因子:
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1997-06
期刊:
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DOI:
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发表时间:
2011-08
期刊:
Wiley Interdisciplinary Reviews: Computational Statistics
影响因子:
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通讯作者:
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DOI:
10.1111/j.2517-6161.1994.tb01976.x
发表时间:
1994
期刊:
Journal of the royal statistical society series b-methodological
影响因子:
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