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连续时间下非参数回归模型的误差密度估计的渐近均方误差(英文)
The Asymptotic Quadric Error of the Error-Density Estimator of Nonparameteric Regression in Continuous Time Processes
【摘要】 本文研究了连续时间下非参数回归的误差密度估计的收敛速度 ,给出了一定条件下误差密度的估计量 ^fT(x)的均方收敛速度 ,详细证明了以下重要结果 :E ^fT(x) -f(x) 2 =O(T-1/ 4)其中f(x)表示误差过程 {et,t≥ 0 }的未知密度 .
【Abstract】 In this paper,we are mainly concerned with the rate of convergence of the error-density estimator of nonparametric regression in continuous time.We have proved that under suitable conditions the kernel density estimator T satisfies E T(x)-f(x)]2=O(T -1/4),where f denotes the unknown density of the error process {e t,t≥0}. 2=O(T -1/4),where f denotes the unknown density of the error process {e t,t≥0}.
【关键词】 收敛速度;
误差密度估计;
连续时间回归模型;
均方收敛;
【Key words】 Rate of convergence,error-density estimator; Continuous-time regression model; mean square convergence;
【Key words】 Rate of convergence,error-density estimator; Continuous-time regression model; mean square convergence;
【基金】 TheprojectsupportedbytheNationalNaturalScienceFoundationofChina(199710 15 )
- 【文献出处】 应用数学 ,Mathematica Applicata , 编辑部邮箱 ,2003年01期
- 【分类号】O212.7
- 【下载频次】53