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引用本文:����,����ǿ,����,����.������ڵľֲ��ͷ������ع鷽��[J].应用概率统计,2016,32(3):270-278.
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Local Penalized Spline Regression Model Based on Range
LI Meng,YANG Lianqiang,JIANG Kun,HE Shengxian.Local Penalized Spline Regression Model Based on Range[J].Chinese Journal of Applied Probability and Statisties,2016,32(3):270-278.
Authors:LI Meng  YANG Lianqiang  JIANG Kun  HE Shengxian
Institution:School of Mathematical Sciences, Anhui University
Abstract:??Inspired by intuitive meanings of truncated power basis's coefficients, the local penalization based on range's linear decreasing function is given in penalized spline regression model. This method gives less penalization to fitting curve where data is with more volatility, which makes fitted curve controls tradeoff between goodness-of-fit and smoothness better. Simulations show that regression models with local penalized spline obtain lower information rules' scores than global penalized spline when the data is with heteroskedasticity.
Keywords:global penalized spline  local panelized spline  
  heteroskedasticity  range  
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