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Least Squares Parameter Estimation for Sparse Functional Varying Coefficient Model

In the present paper, we study functional varying coefficient model in which both the response and the predictor are functions. We give estimates of the intercept and the slope functions in the case that the observations are sparse and noise-contaminated longitudinal data by using least squares repr...

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Главные авторы: Behdad Mostafaiy, Mohammad Reza Faridrohani
Формат: Artigo
Язык:Inglês
Опубликовано: Springer 2017-08-01
Серии:Journal of Statistical Theory and Applications (JSTA)
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Online-ссылка:https://www.atlantis-press.com/article/25883866.pdf
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