Consider the nonparametric regression model Y=go(T)+u,where Y is real-valued, u is a random error,T ranges over a nondegenerate compact interval,say[0,1],and go(·)is an unknown regression function,which is m...Consider the nonparametric regression model Y=go(T)+u,where Y is real-valued, u is a random error,T ranges over a nondegenerate compact interval,say[0,1],and go(·)is an unknown regression function,which is m(m≥0)times continuously differentiable and its ruth derivative,g<sub>0</sub><sup>(m)</sup>,satisfies a H■lder condition of order γ(m +γ】1/2).A piecewise polynomial L<sub>1</sub>- norm estimator of go is proposed.Under some regularity conditions including that the random errors are independent but not necessarily have a common distribution,it is proved that the rates of convergence of the piecewise polynomial L<sub>1</sub>-norm estimator are o(n<sup>-2(m+γ)+1/m+γ-1/δ</sup>almost surely and o(n<sup>-2(m+γ)+1/m+γ-δ</sup>)in probability,which can arbitrarily approach the optimal rates of convergence for nonparametric regression,where δ is any number in (0, min((m+γ-1/2)/3,γ)).展开更多
基金Supported by the National Natural Science Foundation of China.
文摘Consider the nonparametric regression model Y=go(T)+u,where Y is real-valued, u is a random error,T ranges over a nondegenerate compact interval,say[0,1],and go(·)is an unknown regression function,which is m(m≥0)times continuously differentiable and its ruth derivative,g<sub>0</sub><sup>(m)</sup>,satisfies a H■lder condition of order γ(m +γ】1/2).A piecewise polynomial L<sub>1</sub>- norm estimator of go is proposed.Under some regularity conditions including that the random errors are independent but not necessarily have a common distribution,it is proved that the rates of convergence of the piecewise polynomial L<sub>1</sub>-norm estimator are o(n<sup>-2(m+γ)+1/m+γ-1/δ</sup>almost surely and o(n<sup>-2(m+γ)+1/m+γ-δ</sup>)in probability,which can arbitrarily approach the optimal rates of convergence for nonparametric regression,where δ is any number in (0, min((m+γ-1/2)/3,γ)).