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固定设计下计算机模型L2校准的渐近性质
引用本文:王彦.固定设计下计算机模型L2校准的渐近性质[J].系统科学与数学,2020(2):252-261.
作者姓名:王彦
作者单位:北京工业大学应用数理学院
基金项目:朝阳区博士后工作经费(2019ZZ39)资助课题。
摘    要:计算机仿真模型广泛应用于工业工程等领域,借助真实的物理观测对计算机模型的校准参数进行估计,可以提高计算机模型的仿真精度.已有文献指出,当物理试验的试验点独立同分布于均匀分布时,计算机模型校准参数的L2估计半参数有效.然而真实的物理试验点往往不满足独立同分布于均匀分布这一条件,文章证明了在固定的试验点下,较准参数L2估计的相合性和渐近正态性,并通过数值模拟验证了L2估计的收敛速度.

关 键 词:L2校准  固定设计  渐近正态性  核岭回归

The Convergence Properties of L2 Calibration for Computer Models Under Fixed Designs
WANG Yan.The Convergence Properties of L2 Calibration for Computer Models Under Fixed Designs[J].Journal of Systems Science and Mathematical Sciences,2020(2):252-261.
Authors:WANG Yan
Institution:(Beijing University of Technology,College of Applied Sciences,Beijing 100124)
Abstract:Computer simulations are widely used in engineering.The input values of the model parameters can significantly affect the accuracy of the computer outputs.When physical observations are available,one can adjust the computer model parameters so that the computer outputs match the physical data.The existing results show that when the physical samples are i.i.d.and subject to uniform distribution,the L2 calibration is semi-parametric efficiency.However,most designs are not i.i.d.,thus,we give the convergence properties of L2 calibration under fixed designs.The convergence rate of L2 calibration is further verified by two numerical examples.
Keywords:L2 calibration  fixed designs  asymptotic normality  kernel ridge regression  
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