کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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1148682 | 957847 | 2012 | 12 صفحه PDF | دانلود رایگان |
In the context of longitudinal data analysis, a random function typically represents a subject that is often observed at a small number of time point. For discarding this restricted condition of observation number of each subject, we consider the semiparametric partially linear regression models with mean function x⊤βx⊤β + g(z), where x and z are functional data. The estimations of ββ and g(z) are presented and some asymptotic results are given. It is shown that the estimator of the parametric component is asymptotically normal. The convergence rate of the estimator of the nonparametric component is also obtained. Here, the observation number of each subject is completely flexible. Some simulation study is conducted to investigate the finite sample performance of the proposed estimators.
Journal: Journal of Statistical Planning and Inference - Volume 142, Issue 9, September 2012, Pages 2518–2529