Generalized ridge estimation of a semiparametric regression model |
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Authors: | Hongchang Hu Shaolin Rao |
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Affiliation: | (1) York University, Toronto, ON, Canada; |
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Abstract: | We considered the following semiparametric regression model T y i = X i T β + s(t i ) + e i (i = 1,2,...,n). First, the generalized ridge estimators of both parameters and non-parameters are given without a restrained design matrix. Second, the generalized ridge estimator will be compared with the penalized least squares estimator under a mean squares error, and some conditions in which the former excels the latter are given. Finally, the validity and feasibility of the method is illustrated by a simulation example. |
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Keywords: | semiparametric regression model generalized ridge estimation penalized least squares estimation mean squares error |
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