Ridge estimation of a semiparametric regression model
Copyright policy )Ridge estimation of a semiparametric regression model
Consider the semiparametric regression model \[ l_i=A_iTX+s(t_i)+\Delta_i,\quad i=1,2,\dots,n. \] Firstly, ridge estimators are attained without a restrained design matrix. Secondly, the ridge estimator will be compared with two steps estimation under mean square error and some conditions in which the former excels the latter are given. Finally, the validity and feasibility of the method are illustrated by a simulation example.
- Wuhan University China (People's Republic of)
- Hubei Normal University China (People's Republic of)
Computational Mathematics, Ridge regression; shrinkage estimators (Lasso), Applied Mathematics, Ridge estimation, Mean square error, Nonparametric regression and quantile regression, Semiparametric regression model, Two steps estimation
Computational Mathematics, Ridge regression; shrinkage estimators (Lasso), Applied Mathematics, Ridge estimation, Mean square error, Nonparametric regression and quantile regression, Semiparametric regression model, Two steps estimation
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