摘要
把基于无截断Bartlett核的长期协方差估计方法推广到函数型数据情形,提出基于无截断Bartlett核的函数重构方法,并通过两种Monte Carlo模拟和2018年沪深300高频数据进行了对比分析.数值模拟和实例分析均表明,文中所提方法的函数重构误差最小,具有一定的稳健性和有效性.
The long-run covariance estimation method based on the Bartlett kernel without truncation is extended to the case of functional data,and a function reconstruction method based on the Bartlett kernel without truncation is proposed.A comparative analysis is carried out by two Monte Carlo simulations and the 2018 CSI 300 high-frequency data.Numerical simulations and example analysis both show that the method proposed in the article has the smallest function reconstruction error,and has certain robustness and effectiveness.
作者
李气芳
苏梽芳
马翠
LI Qifang;SU Zhifang;MA Cui(School of Mathematics and Statistics,Minnan Normal University,Zhangzhou,Fujian 363000,China;School of Economics and Finance,Huaqiao University,Quanzhou,Fujian 362021,China;The First Vocational Secondary School of Zhangzhou,Zhangzhou,Fujian 363000,China)
出处
《闽南师范大学学报（自然科学版）》
2021年第2期1-6,共6页
Journal of Minnan Normal University：Natural Science
基金
国家自然科学基金面上项目(11871259)
福建省自然科学基金面上项目(2020J01794)
福建省中青年教师教育科研项目(JAT190371)。
关键词
函数主成分
函数重构
长期协方差函数
无截断Bartlett核
function principal component
function reconstruction
long-run covariance function
Bartlett kernel without truncation
