引用本文:陈性敏,高超.递推局部线性回归估计及其应用[J].控制理论与应用,2013,30(4):482~491.[点击复制]
CHEN Xing-min,GAO Chao.Recursive local linear regression estimation and its applications[J].Control Theory and Technology,2013,30(4):482~491.[点击复制]
递推局部线性回归估计及其应用
Recursive local linear regression estimation and its applications
摘要点击 4019  全文点击 2273  投稿时间:2012-10-18  修订日期:2013-01-07
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DOI编号  10.7641/CTA.2013.21076
  2013,30(4):482-491
中文关键词  局部线性回归  递推辨识  核估计  强一致性  非线性ARX系统
英文关键词  local linear regression  recursive identification  kernel estimation  strong consistency  nonlinear ARX systems
基金项目  国家自然科学基金资助项目(61203118); 中央高校基本科研业务费专项资金资助项目.
作者单位E-mail
陈性敏* 大连理工大学 数学科学学院 xingmin.chen@gmail.com 
高超 北京信息控制研究所  
中文摘要
      在非参数统计中, 局部多项式回归是重要的工具, 然而以往研究的算法基本都是非递推的. 本文研究递推的局部线性回归估计及其应用. 首先推导出递推算法, 给出了回归函数及其导函数的非参数估计. 在一定的条件下, 证明了算法的强一致性. 并且通过仿真例子研究了它在非线性条件异方差模型的回归函数估计和非线性ARX(nonlinear autoregressive system with exogenous inputs, NARX)系统辨识中的应用.
英文摘要
      In nonparametric statistics, local polynomial regression is one of the most important tools. However, almost the previous work is based on nonrecursive algorithms. We investigate the recursive local linear regression estimation. The recursive algorithms are derived for the nonparametric estimation of the regression function and its derivative. Strong consistence of the estimates is established under reasonable conditions. The applications to estimation of the regression model with nonlinear conditional heteroskedasticity and identification of the nonlinear ARX (NARX) system are demonstrated by numerical simulation.