摘要
本文在ρ混合样本下讨论Gasser和Müller提出的一类非参数核回归估计的强相合性.在较弱的条件下,证明了该估计的强相合性与一致强相合性.
For ρ-mixing samples,we discuss the strong consistency of the nonparametric kernel regression estimator proposed by Gasser and Müller.Under more weaker conditions,its strong consistency and uniformly strong consistency are proved.
作者
杨秀桃
杨昕
刘莲花
杨善朝
YANG Xiutao;YANG Xin;LIU Lianhua;YANG Shanchao(Teaching and Research Department of Public Mathematics,Networking School,Haikou College of Economics,Haikou,571127,China;Department of Mathematics,Guilin University of Aerospace Technology,Guilin,541004,China;School of Public Health,Hainan Medical University,Haikou,571199,China;School of Mathematics and Statistics,Guangxi Normal University,Guilin,541004,China)
出处
《应用概率统计》
CSCD
北大核心
2020年第2期138-150,共13页
Chinese Journal of Applied Probability and Statistics
基金
海南省自然科学基金项目(批准号:117173、118MS085)
国家自然科学基金项目(批准号:11461009)资助.
关键词
ρ混合样本
非参数核回归估计
强相合性
一致强相合性
ρ-mixing samples
nonparametric kernel regression estimator
strong consistency
uniformly strong consistency
