In this paper, we study the strong consistency and convergence partitioning estimate of nonparametric regression function under the sample that is α sequence taking values in R^d × R^1 with identical distributio...In this paper, we study the strong consistency and convergence partitioning estimate of nonparametric regression function under the sample that is α sequence taking values in R^d × R^1 with identical distribution. rate of modified （（Xi,Yi）,i 〉 1} .展开更多
Strong uniform consistency rates are given for kernel type estimatorsof the conditional function with （?）-mixing sample.Especially,for nonparametricestimators of kernel density,the regression function when Y is boun...Strong uniform consistency rates are given for kernel type estimatorsof the conditional function with （?）-mixing sample.Especially,for nonparametricestimators of kernel density,the regression function when Y is bounded,conditionaldf’s,L-smoothing and M-smoothing,we obtain the same rate O(（n/log n）<sup>-1/3</sup>)as in the i.i.d.sample established by H（?）rdle,Janssen and Serfling.展开更多
文摘In this paper, we study the strong consistency and convergence partitioning estimate of nonparametric regression function under the sample that is α sequence taking values in R^d × R^1 with identical distribution. rate of modified （（Xi,Yi）,i 〉 1} .
基金Research supported by the Natural Science Foundation of China
文摘Strong uniform consistency rates are given for kernel type estimatorsof the conditional function with （?）-mixing sample.Especially,for nonparametricestimators of kernel density,the regression function when Y is bounded,conditionaldf’s,L-smoothing and M-smoothing,we obtain the same rate O(（n/log n）<sup>-1/3</sup>)as in the i.i.d.sample established by H（?）rdle,Janssen and Serfling.
